From 6caafdb79483c6e470d9c6af26b831d7daf4626e Mon Sep 17 00:00:00 2001
From: LEGSTECH Optimizer <legstech@optimizer.local>
Date: Sat, 25 Apr 2026 11:39:17 +0000
Subject: [PATCH] =?UTF-8?q?feat:=20open-source=20release=20=E2=80=94=20AI-?=
 =?UTF-8?q?driven=20autonomous=20optimization=20with=20live=20visibility?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Major upgrade making the AI loop visible and the project ready for public release.

UI / UX
- Live AI Thinking Feed: streams reasoning, decisions, and outcomes per iteration
- Parameter Changes panel: prev → new + reason for every AI-driven edit
- Validation Activity panel: out-of-sample + sensitivity runs with live metrics
- Early Termination banner: surfaces why optimization stopped (targets met, no profit, budget, stuck, user stop)
- 3-phase tracker renamed Exploration / Iteration / Validation with live N/total
- Best Result modal exposes Evolution Path showing how the AI arrived at the winner
- Run-detail modal accessible from every recent run row
- Setup form validation (dates, walk-forward order, params selection, AI targets)
- Pause button removed; misleading sidebar nav consolidated to Dashboard / New Run / Reports / Source

Backend
- AIGuidedLoop streams ai_thinking, param_changes, ai_targets_met, ai_stuck
- Pipeline emits validation_start / validation_run_start / validation_run_complete / validation_done
- Pipeline emits early_termination on every early-stop path
- /api/best_result returns best run + full evolution chain
- /api/run/<id> + /api/runs sorted by ts
- AIReasoner falls back to ANTHROPIC_API_KEY env var when config is a placeholder
- Demo mode (APEX_DEMO_MODE=1) generates deterministic synthetic backtests so judges can run end-to-end without MT5

Open-source readiness
- README.md with pitch, demo flow, architecture diagram, quickstart, event reference
- LICENSE (MIT)
- config.example.yaml template (config.yaml now git-ignored)
- requirements.txt: added anthropic / requests / psutil / beautifulsoup4, capped majors
- .gitignore: secrets, *.set, scratch screenshots, ea_registry.yaml
- demo/run_demo.py: one-command offline demo runner
- 10 polished screenshots for README + judge review
---
 .gitignore                            |   30 +-
 LICENSE                               |   21 +
 README.md                             |  207 ++
 analysis/ai_reasoner.py               |  459 +++++
 analysis/ai_reasoner_config.py        |   46 +
 app.py                                |  340 +++-
 config.example.yaml                   |  122 ++
 config.yaml                           |  104 -
 demo/__init__.py                      |    0
 demo/run_demo.py                      |  142 ++
 ea_registry.yaml                      |   35 -
 optimizer/ai_guided_loop.py           |  576 ++++++
 optimizer/pipeline.py                 |  601 +++++-
 optimizer/session_config.py           |   25 +-
 optimizer_loop.py                     |   48 +
 requirements.txt                      |   52 +-
 screenshots/best_result_modal.png     |  Bin 0 -> 170392 bytes
 screenshots/dashboard.png             |  Bin 0 -> 192196 bytes
 screenshots/landing.png               |  Bin 0 -> 265689 bytes
 screenshots/settings_broker.png       |  Bin 0 -> 109435 bytes
 screenshots/settings_modal.png        |  Bin 0 -> 118685 bytes
 screenshots/settings_mt5.png          |  Bin 0 -> 127805 bytes
 screenshots/settings_thresholds.png   |  Bin 0 -> 115978 bytes
 screenshots/setup.png                 |  Bin 0 -> 104063 bytes
 screenshots/setup_autonomous_open.png |  Bin 0 -> 90095 bytes
 screenshots/setup_bottom.png          |  Bin 0 -> 87096 bytes
 ui/static/css/style.css               |  107 +
 ui/static/js/dashboard.js             | 2101 ++++++++++++++++----
 ui/templates/dashboard.html           | 2569 ++++++++++++++++++++++---
 ui/templates/landing.html             |  661 ++++---
 ui/templates/setup.html               |  413 +++-
 31 files changed, 7546 insertions(+), 1113 deletions(-)
 create mode 100644 LICENSE
 create mode 100644 README.md
 create mode 100644 analysis/ai_reasoner.py
 create mode 100644 analysis/ai_reasoner_config.py
 create mode 100644 config.example.yaml
 delete mode 100644 config.yaml
 create mode 100644 demo/__init__.py
 create mode 100644 demo/run_demo.py
 delete mode 100644 ea_registry.yaml
 create mode 100644 optimizer/ai_guided_loop.py
 create mode 100644 screenshots/best_result_modal.png
 create mode 100644 screenshots/dashboard.png
 create mode 100644 screenshots/landing.png
 create mode 100644 screenshots/settings_broker.png
 create mode 100644 screenshots/settings_modal.png
 create mode 100644 screenshots/settings_mt5.png
 create mode 100644 screenshots/settings_thresholds.png
 create mode 100644 screenshots/setup.png
 create mode 100644 screenshots/setup_autonomous_open.png
 create mode 100644 screenshots/setup_bottom.png

diff --git a/.gitignore b/.gitignore
index cb74696..56d1be3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -24,9 +24,33 @@ Reports/
 # Keep the optimizer database (optional — remove this line to commit it)
 optimizer.db
 
-# ── Sensitive Config (DO NOT COMMIT BROKER CREDENTIALS) ──────────────────────
-# config.yaml contains MT5 paths — safe to commit but exclude if it had passwords
-# config.secret.yaml
+# ── Sensitive Config (DO NOT COMMIT — contains API keys) ────────────────────
+# Users copy config.example.yaml → config.yaml and fill in their key locally.
+config.yaml
+.env
+.env.local
+*.secret.yaml
+*.secret.yml
+config.secret.yaml
+
+# ── EA Registry (machine-specific paths) ─────────────────────────────────────
+ea_registry.yaml
+
+# ── Generated set files ──────────────────────────────────────────────────────
+*.set
+!**/templates/*.set
+
+# ── Screenshots scratch (Playwright debug + health-test artifacts) ──────────
+screenshots/health_*.png
+screenshots/health_*.json
+screenshots/debug*.png
+screenshots/playwright_*.png
+screenshots/*.py
+screenshots/crop_*.png
+
+# ── Claude session artifacts ─────────────────────────────────────────────────
+Claude_Code_session*
+.claude/sessions/
 
 # ── Logs ──────────────────────────────────────────────────────────────────────
 *.log
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..228f18a
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 APEX MT5 Optimizer contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..96b91b1
--- /dev/null
+++ b/README.md
@@ -0,0 +1,207 @@
+# APEX — AI‑Powered MT5 EA Optimizer
+
+> **An AI trader thinking out loud while it tests, fails, and improves a strategy.**
+
+APEX is an autonomous optimizer for MetaTrader 5 Expert Advisors. Instead of brute‑forcing
+parameters with grid search, an LLM reads each backtest result, decides which parameter to
+change and why, then runs the next backtest — iterating toward profit‑factor / drawdown /
+Calmar targets you set. Every reasoning step streams live to a dashboard.
+
+---
+
+## Why this is different
+
+| Traditional optimizers | APEX |
+| --- | --- |
+| Brute‑force grid / genetic search | AI reads each result, **decides** what to change |
+| Black box — see only final winner | Live **thinking feed** + per‑iteration param diffs |
+| No notion of *why* a config works | Stores AI analysis next to every run |
+| Stops after N iterations | Stops when **quality targets are met** (early exit) |
+| One‑shot validation | Out‑of‑sample **+ sensitivity** with live progress |
+
+---
+
+## Demo
+
+![Dashboard](screenshots/dashboard.png)
+
+The dashboard shows three live phases — **Exploration → Iteration → Validation** — with the
+AI's reasoning streaming on the right, parameter changes per iteration in the centre, and an
+out‑of‑sample/sensitivity validation panel that updates as MT5 finishes each test.
+
+Other views: [setup wizard](screenshots/setup.png) · [settings modal](screenshots/settings_modal.png)
+
+---
+
+## How it works
+
+```
+┌──────────────────────────────────────────────────────────────────────────┐
+│                       APEX OPTIMIZATION LOOP                             │
+│                                                                          │
+│   Phase 1: EXPLORATION                                                   │
+│     Latin‑Hypercube sample N parameter sets → run in MT5 Strategy Tester │
+│     → score with Calmar / PF / MFE / session‑stability / recovery        │
+│                                                                          │
+│   Phase 2: AI ITERATION (autonomous loop)                                │
+│     ┌──► Claude reads full history + targets + parameter schema          │
+│     │      ↓                                                             │
+│     │    Claude returns: { changes:[{param,value,reason}], confidence }  │
+│     │      ↓                                                             │
+│     │    Apply changes (clamped to schema bounds), dedupe, run backtest  │
+│     │      ↓                                                             │
+│     │    Stream `ai_thinking` + `param_changes` events to UI             │
+│     │      ↓                                                             │
+│     └──── Targets met? → exit early.  Stuck? → random escape.            │
+│                                                                          │
+│   Phase 3: VALIDATION                                                    │
+│     Out‑of‑sample run on unseen dates + ±20% sensitivity probe on the    │
+│     top parameter → verdict: RECOMMENDED / RISKY / NOT_RELIABLE          │
+│                                                                          │
+│   Output: ranked .set file + per‑run report folder + final verdict       │
+└──────────────────────────────────────────────────────────────────────────┘
+```
+
+The AI loop lives in [`optimizer/ai_guided_loop.py`](optimizer/ai_guided_loop.py); the
+reasoner contract is in [`analysis/ai_reasoner.py`](analysis/ai_reasoner.py); event emission
+to the UI flows through [`optimizer/pipeline.py`](optimizer/pipeline.py) via SocketIO.
+
+---
+
+## Quick start
+
+### 1. Clone + install
+
+```bash
+git clone https://github.com/<your-user>/MT5_Optimizer.git
+cd MT5_Optimizer
+python -m venv .venv
+.venv\Scripts\activate            # Windows
+# source .venv/bin/activate       # macOS/Linux
+pip install -r requirements.txt
+```
+
+### 2. Configure
+
+Copy the example config and fill it in:
+
+```bash
+cp config.example.yaml config.yaml
+```
+
+Set your Anthropic API key (get one at <https://console.anthropic.com/>):
+
+```bash
+# Option A — environment variable (recommended)
+setx ANTHROPIC_API_KEY "sk-ant-..."     # Windows
+export ANTHROPIC_API_KEY="sk-ant-..."   # macOS/Linux
+
+# Option B — paste into config.yaml under ai.anthropic_api_key
+```
+
+Edit `config.yaml` to match your local MT5 install paths under `mt5:` (terminal exe,
+AppData path, MQL5 Files path).
+
+### 3. Launch
+
+```bash
+python app.py
+```
+
+Open <http://localhost:5000>. Register your EA on the **Setup** page, set thresholds,
+hit **Start**, and watch the AI think.
+
+### Demo mode (no MT5 required)
+
+Don't have MT5 installed? Run the offline demo that feeds synthetic backtest results
+through the same AI loop and dashboard:
+
+```bash
+python -m demo.run_demo
+```
+
+This is the path to use if you're a hackathon judge — you'll see the full thinking feed,
+parameter‑change panel, validation phase, and verdict screen without needing a Windows
+machine with MT5.
+
+---
+
+## Configuration cheatsheet
+
+| Key | What it does |
+| --- | --- |
+| `ai.enabled` | Master toggle for the AI reasoning layer. |
+| `ai.model` | `claude-opus-4-7` (best), `claude-sonnet-4-6` (balanced), `claude-haiku-4-5` (fast). |
+| `thresholds.min_profit_factor` / `min_calmar` | Quality gates a result must clear. |
+| `optimization.max_iterations` | Hard cap on AI loop iterations. |
+| `mt5.terminal_exe` | Full path to `terminal64.exe`. |
+| `periods.train_*` / `validate_*` / `oos_*` | Train + walk‑forward validation date ranges. |
+
+The full schema lives in [`config.example.yaml`](config.example.yaml) with comments.
+
+---
+
+## Project layout
+
+```
+MT5_Optimizer/
+├── app.py                    Flask + SocketIO server (entry point)
+├── config.example.yaml       Configuration template
+├── analysis/
+│   └── ai_reasoner.py        Claude API client (analyze + suggest_next_params)
+├── optimizer/
+│   ├── pipeline.py           3‑phase pipeline orchestrator
+│   ├── ai_guided_loop.py     Autonomous AI iteration loop
+│   ├── result_ranker.py      Scoring & ranking of runs
+│   └── session_config.py     Per‑run config dataclass
+├── ea/
+│   └── schema.py             EA parameter schema + clamp/validation
+├── mt5/                      MT5 launcher, ini builder, html report parser
+├── reports/
+│   └── writer.py             Per‑run HTML/CSV/JSON output
+├── ui/
+│   ├── templates/            dashboard.html, setup.html, reports_index.html
+│   └── static/js/dashboard.js  All client‑side logic
+└── tests/
+```
+
+See [`PROJECT_HANDOFF.md`](PROJECT_HANDOFF.md) for a deeper architectural tour.
+
+---
+
+## Live events (SocketIO)
+
+The dashboard subscribes to these — useful if you want to plug a different UI on top:
+
+| Event | When it fires | Payload (key fields) |
+| --- | --- | --- |
+| `phase_start` | Each phase begins | `phase`, `total`, `mode` |
+| `run_complete` | Any backtest finishes | `run_id`, `phase`, `net_profit`, `profit_factor`, `calmar`, `max_drawdown`, `score`, `params` |
+| `ai_thinking` | AI narrates a decision | `msg`, `kind` (`info`/`reasoning`/`decision`/`success`/`warning`/`hypothesis`), `iteration`, `phase` |
+| `ai_iteration_start` / `ai_iteration_complete` | Each AI loop iteration | `iteration`, `analysis`, `change_records`, `confidence`, `goal_status` |
+| `param_changes` | Per‑iteration parameter diff | `iteration`, `changes:[{param, from, to, reason}]`, `confidence` |
+| `validation_start` / `validation_run_start` / `validation_run_complete` / `validation_done` | Phase 3 visibility | `kind` (`oos`/`sensitivity`), metrics, `passing` |
+| `early_termination` | Pipeline stops before max_iterations | `reason` (`targets_met`/`no_profit`/`budget_exhausted`/`stuck_escape`/`user_stop`), `message`, `details` |
+| `optimization_complete` | Run finished | `verdict`, `best_run_id`, `set_file_url`, full metrics |
+
+---
+
+## Contributing
+
+Bug reports + PRs welcome. The codebase is intentionally small enough to read in an hour:
+
+- `optimizer/pipeline.py` orchestrates phases.
+- `optimizer/ai_guided_loop.py` is the autonomous loop.
+- `ui/static/js/dashboard.js` is one file; no frontend build step.
+
+Run tests with `pytest`. There's no CI yet — fix that and we'll merge it.
+
+---
+
+## License
+
+MIT — see [LICENSE](LICENSE). Use it, fork it, ship it.
+
+Built with [Anthropic Claude](https://claude.com/) for the reasoning layer and
+[MetaTrader 5](https://www.metatrader5.com/) for the backtests. APEX is independent of and
+not endorsed by either.
diff --git a/analysis/ai_reasoner.py b/analysis/ai_reasoner.py
new file mode 100644
index 0000000..ddc3848
--- /dev/null
+++ b/analysis/ai_reasoner.py
@@ -0,0 +1,459 @@
+"""
+analysis/ai_reasoner.py
+AI Reasoning Layer — uses Claude API to interpret backtest results,
+identify patterns across runs, and suggest intelligent parameter changes.
+
+Two modes:
+  1. analyze()              → AIInsight  (per-run diagnostic, display-only)
+  2. suggest_next_params()  → AIParamSuggestion  (autonomous loop — drives next test)
+
+Usage:
+    reasoner = AIReasoner(api_key="sk-ant-...")
+    insight  = reasoner.analyze(findings, metrics, run_history)
+    suggest  = reasoner.suggest_next_params(current_params, schema_info, history, targets)
+"""
+from __future__ import annotations
+
+import json
+import os
+from dataclasses import dataclass
+from typing import Optional
+
+import requests
+from loguru import logger
+
+from data.models import Finding, RunMetrics
+
+
+# ── Output models ─────────────────────────────────────────────────────────────
+
+@dataclass
+class AIInsight:
+    """Structured AI reasoning output for one optimization run."""
+    headline:     str                   # One-sentence diagnosis
+    diagnosis:    str                   # 2-3 sentence explanation of WHY
+    patterns:     list[str]             # Key patterns in plain English
+    suggestions:  list[dict]            # [{param, from, to, reason}]
+    confidence:   str                   # "high" | "medium" | "low"
+    risk_flags:   list[str]             # Warnings (overfitting risk, data issues etc)
+    run_id:       str = ""
+    error:        Optional[str] = None  # Set if API call failed
+
+    def to_dict(self) -> dict:
+        return {
+            "headline":    self.headline,
+            "diagnosis":   self.diagnosis,
+            "patterns":    self.patterns,
+            "suggestions": self.suggestions,
+            "confidence":  self.confidence,
+            "risk_flags":  self.risk_flags,
+            "run_id":      self.run_id,
+            "error":       self.error,
+        }
+
+
+@dataclass
+class AIParamSuggestion:
+    """
+    Output of suggest_next_params() — drives the autonomous optimization loop.
+    Contains concrete parameter values for the next backtest.
+    """
+    analysis:    str          # What the AI observed and why it's making these changes
+    changes:     list[dict]   # [{param, value, reason}] — specific values, not deltas
+    confidence:  float        # 0.0–1.0
+    goal_status: dict         # {profit_factor_met, drawdown_ok, calmar_met}
+    error:       Optional[str] = None
+
+
+# ── Reasoner ──────────────────────────────────────────────────────────────────
+
+class AIReasoner:
+    """
+    Calls Claude API to reason about backtest results.
+    Falls back gracefully if API key is missing or call fails.
+    """
+
+    MODEL   = "claude-sonnet-4-6"
+    API_URL = "https://api.anthropic.com/v1/messages"
+    TIMEOUT = 30  # seconds
+
+    def __init__(self, api_key: Optional[str] = None):
+        # If the caller passes a placeholder like "${ANTHROPIC_API_KEY}" or an
+        # empty string, treat it as missing and fall back to the env var.
+        candidate = (api_key or "").strip()
+        if not candidate or candidate.startswith("${") or candidate in ("YOUR_API_KEY", "sk-ant-..."):
+            candidate = os.environ.get("ANTHROPIC_API_KEY", "").strip()
+        self.api_key = candidate
+        self.enabled = bool(self.api_key)
+        if not self.enabled:
+            logger.warning(
+                "AIReasoner: No API key found. Set ANTHROPIC_API_KEY in your environment "
+                "or in config.yaml under ai.anthropic_api_key. AI insights will be skipped."
+            )
+
+    # ── Public ────────────────────────────────────────────────────────────────
+
+    def analyze(
+        self,
+        findings:    list[Finding],
+        metrics:     RunMetrics,
+        run_history: list[dict],   # list of {run_id, score, calmar, pf, params, phase}
+        current_params: dict = {},
+    ) -> AIInsight:
+        """
+        Main entry point. Returns an AIInsight.
+        Never raises — always returns something useful.
+        """
+        if not self.enabled:
+            return self._fallback_insight(findings, metrics)
+
+        prompt = self._build_prompt(findings, metrics, run_history, current_params)
+
+        try:
+            raw = self._call_claude(prompt)
+            insight = self._parse_response(raw, metrics.run_id)
+            insight.run_id = metrics.run_id
+            logger.info(f"AIReasoner: insight generated for {metrics.run_id} — {insight.confidence} confidence")
+            return insight
+        except Exception as e:
+            logger.error(f"AIReasoner API error: {e}")
+            fallback = self._fallback_insight(findings, metrics)
+            fallback.error = str(e)
+            return fallback
+
+    # ── Prompt builder ────────────────────────────────────────────────────────
+
+    def _build_prompt(
+        self,
+        findings:    list[Finding],
+        metrics:     RunMetrics,
+        run_history: list[dict],
+        current_params: dict,
+    ) -> str:
+
+        # Serialize findings
+        findings_text = "\n".join([
+            f"- [{f.severity.upper()}] {f.analyzer}: {f.description} "
+            f"(confidence={f.confidence:.2f}, est. impact=${f.impact_estimate_pnl:.0f})"
+            for f in findings[:8]  # cap at 8 to stay within context
+        ]) or "No findings generated."
+
+        # Serialize run history (last 5 runs)
+        history_text = ""
+        if run_history:
+            history_text = "\n".join([
+                f"- {r.get('run_id','?')} | score={r.get('score',0):.4f} | "
+                f"calmar={r.get('calmar',0):.3f} | pf={r.get('pf',0):.3f} | phase={r.get('phase','?')}"
+                for r in run_history[-5:]
+            ])
+        else:
+            history_text = "This is the first run."
+
+        # Serialize key current params
+        key_params = {k: v for k, v in current_params.items()
+                      if any(kw in k.lower() for kw in
+                             ["risk", "trail", "sl", "tp", "rr", "session", "atr", "spread", "be"])}
+        params_text = json.dumps(key_params, indent=2) if key_params else "{}"
+
+        return f"""You are an expert algorithmic trading system analyst specializing in MetaTrader 5 Expert Advisors and systematic trading strategy optimization.
+
+You are analyzing the results of an automated EA optimization run. Your job is to:
+1. Diagnose WHY the EA is performing the way it is
+2. Identify the most important patterns
+3. Suggest specific, actionable parameter changes with clear reasoning
+
+## Current Run Metrics
+- Run ID: {metrics.run_id}
+- Net Profit: ${metrics.net_profit:.2f}
+- Profit Factor: {metrics.profit_factor:.3f}
+- Calmar Ratio: {metrics.calmar_ratio:.3f}
+- Max Drawdown: {metrics.max_drawdown_pct*100:.1f}%
+- Total Trades: {metrics.total_trades}
+- Win Rate: {metrics.win_rate*100:.1f}%
+- Sharpe Ratio: {metrics.sharpe_ratio:.3f}
+- Reversal Rate: {getattr(metrics, 'reversal_rate', None) and f"{metrics.reversal_rate*100:.1f}%" or "N/A"}
+- Avg MFE Capture: {getattr(metrics, 'avg_mfe_capture', None) and f"{metrics.avg_mfe_capture*100:.1f}%" or "N/A"}
+- Composite Score: {metrics.composite_score:.4f}
+
+## Analysis Findings
+{findings_text}
+
+## Run History (recent runs)
+{history_text}
+
+## Current Key Parameters
+{params_text}
+
+## Instructions
+Respond ONLY with a valid JSON object. No preamble, no markdown, no backticks.
+The JSON must have exactly these keys:
+
+{{
+  "headline": "One sentence diagnosis (max 15 words)",
+  "diagnosis": "2-3 sentences explaining WHY the EA is performing this way. Be specific about the root cause.",
+  "patterns": ["pattern 1 in plain English", "pattern 2", "pattern 3"],
+  "suggestions": [
+    {{"param": "InpTrailStartPips", "from": 20, "to": 15, "reason": "Why this change helps"}},
+    {{"param": "InpRRRatio", "from": 1.5, "to": 2.0, "reason": "Why this change helps"}}
+  ],
+  "confidence": "high|medium|low",
+  "risk_flags": ["any overfitting concerns, data issues, or warnings"]
+}}
+
+Be direct and technical. The user is an experienced forex trader. Max 2-3 suggestions. Focus on what will actually move the needle."""
+
+    # ── API call ──────────────────────────────────────────────────────────────
+
+    def _call_claude(self, prompt: str) -> str:
+        headers = {
+            "Content-Type":    "application/json",
+            "x-api-key":       self.api_key,
+            "anthropic-version": "2023-06-01",
+        }
+        body = {
+            "model":      self.MODEL,
+            "max_tokens": 1024,
+            "messages":   [{"role": "user", "content": prompt}],
+        }
+
+        resp = requests.post(
+            self.API_URL,
+            headers=headers,
+            json=body,
+            timeout=self.TIMEOUT,
+        )
+
+        if resp.status_code != 200:
+            raise RuntimeError(
+                f"Claude API returned {resp.status_code}: {resp.text[:300]}"
+            )
+
+        data = resp.json()
+        return data["content"][0]["text"]
+
+    # ── Response parser ───────────────────────────────────────────────────────
+
+    def _parse_response(self, raw: str, run_id: str) -> AIInsight:
+        """Parse Claude's JSON response into an AIInsight."""
+        # Strip any accidental markdown fences
+        text = raw.strip()
+        if text.startswith("```"):
+            lines = text.split("\n")
+            text = "\n".join(lines[1:-1]) if lines[-1].strip() == "```" else "\n".join(lines[1:])
+
+        data = json.loads(text)
+
+        return AIInsight(
+            headline=data.get("headline", "Analysis complete."),
+            diagnosis=data.get("diagnosis", ""),
+            patterns=data.get("patterns", []),
+            suggestions=data.get("suggestions", []),
+            confidence=data.get("confidence", "medium"),
+            risk_flags=data.get("risk_flags", []),
+            run_id=run_id,
+        )
+
+    # ── Autonomous loop: parameter suggestion ─────────────────────────────────
+
+    def suggest_next_params(
+        self,
+        current_best_params: dict,
+        schema_info: list[dict],       # [{name, type, min, max, step, current}]
+        iteration_history: list[dict], # [{iteration, run_id, score, pf, calmar, dd, params_changed}]
+        targets: dict,                 # {min_profit_factor, max_drawdown_pct, min_calmar}
+    ) -> AIParamSuggestion:
+        """
+        Ask the AI what parameter set to test next in the autonomous loop.
+        Returns concrete values for each parameter to change.
+        Never raises — returns an error suggestion on failure.
+        """
+        if not self.enabled:
+            return AIParamSuggestion(
+                analysis="AI not available — no API key configured.",
+                changes=[],
+                confidence=0.0,
+                goal_status={},
+                error="no_api_key",
+            )
+
+        prompt = self._build_evolution_prompt(
+            current_best_params, schema_info, iteration_history, targets
+        )
+
+        try:
+            raw = self._call_claude(prompt)
+            return self._parse_suggestion(raw)
+        except Exception as e:
+            logger.error(f"AIReasoner.suggest_next_params failed: {e}")
+            return AIParamSuggestion(
+                analysis=f"AI call failed: {e}",
+                changes=[],
+                confidence=0.0,
+                goal_status={},
+                error=str(e),
+            )
+
+    def _build_evolution_prompt(
+        self,
+        current_best_params: dict,
+        schema_info: list[dict],
+        iteration_history: list[dict],
+        targets: dict,
+    ) -> str:
+        """Build the evolution prompt for the autonomous loop."""
+
+        # Format parameter schema table
+        schema_rows = []
+        for p in schema_info:
+            current_val = current_best_params.get(p["name"], p.get("default", "?"))
+            schema_rows.append(
+                f"  {p['name']:<30} | {p['type']:<6} | {p.get('min','?'):>8} – {p.get('max','?'):<8} "
+                f"| step={p.get('step','?'):<6} | CURRENT={current_val}"
+            )
+        schema_table = "\n".join(schema_rows) or "  (no optimizable parameters)"
+
+        # Format iteration history
+        if iteration_history:
+            hist_rows = []
+            for h in iteration_history[-15:]:  # last 15 to stay in context
+                changes_str = ", ".join(
+                    f"{c['param']}={c['value']}" for c in h.get("changes", [])
+                ) or "baseline"
+                hist_rows.append(
+                    f"  iter={h.get('iteration','?'):>3} | score={h.get('score',0):.4f} | "
+                    f"pf={h.get('pf',0):.2f} | calmar={h.get('calmar',0):.2f} | "
+                    f"dd={h.get('dd',0):.1f}% | trades={h.get('trades',0)} | "
+                    f"changes=[{changes_str}]"
+                )
+            history_table = "\n".join(hist_rows)
+        else:
+            history_table = "  (no iterations yet — this is the first AI suggestion)"
+
+        # Format targets
+        target_pf      = targets.get("min_profit_factor", 1.5)
+        target_dd      = targets.get("max_drawdown_pct", 20.0)
+        target_calmar  = targets.get("min_calmar", 0.5)
+
+        return f"""You are an expert MetaTrader 5 EA optimization engine running in autonomous mode.
+
+Your job is to decide EXACTLY which parameters to change and to what SPECIFIC VALUES for the next backtest.
+You must reason from the history of tried configurations and move intelligently toward the targets.
+
+## Optimization Targets (ALL must be met to stop)
+- Profit Factor   ≥ {target_pf}
+- Max Drawdown    ≤ {target_dd}%
+- Calmar Ratio    ≥ {target_calmar}
+
+## Optimizable Parameter Schema
+{schema_table}
+
+## Iteration History (most recent 15, newest last)
+{history_table}
+
+## Your Task
+1. Identify which metrics are furthest from their targets
+2. Identify which parameter changes correlate with improvements in those metrics
+3. Identify unexplored regions of the parameter space
+4. Choose 1–3 parameters to change and provide SPECIFIC VALUES within valid range
+
+Rules:
+- Values MUST be within [min, max] and snap to valid step increments
+- Do NOT suggest a combination already tested in the history above
+- Make changes that are logically motivated — explain the reasoning
+- If previous attempts moved in one direction and improved scores, continue that direction
+- If previous attempts got stuck, try a different parameter or a larger change
+
+Respond ONLY with valid JSON (no markdown, no extra text):
+{{
+  "analysis": "2-3 sentences: what pattern you see in the history and WHY you are making these specific changes",
+  "changes": [
+    {{"param": "ExactParamName", "value": 1.5, "reason": "one-line reason"}},
+    {{"param": "AnotherParam",  "value": 12,  "reason": "one-line reason"}}
+  ],
+  "confidence": 0.75,
+  "goal_status": {{
+    "profit_factor_met": false,
+    "drawdown_ok": true,
+    "calmar_met": false
+  }}
+}}"""
+
+    def _parse_suggestion(self, raw: str) -> AIParamSuggestion:
+        """Parse AI suggestion response into AIParamSuggestion."""
+        text = raw.strip()
+        if text.startswith("```"):
+            lines = text.split("\n")
+            text = "\n".join(lines[1:-1]) if lines[-1].strip() == "```" else "\n".join(lines[1:])
+
+        data = json.loads(text)
+
+        # Normalize confidence to float
+        conf = data.get("confidence", 0.5)
+        if isinstance(conf, str):
+            conf = {"high": 0.85, "medium": 0.6, "low": 0.3}.get(conf.lower(), 0.5)
+        conf = float(max(0.0, min(1.0, conf)))
+
+        return AIParamSuggestion(
+            analysis=data.get("analysis", ""),
+            changes=data.get("changes", []),
+            confidence=conf,
+            goal_status=data.get("goal_status", {}),
+        )
+
+    # ── Fallback (no API key or error) ────────────────────────────────────────
+
+    def _fallback_insight(self, findings: list[Finding], metrics: RunMetrics) -> AIInsight:
+        """
+        Rule-based fallback when Claude API is unavailable.
+        Still useful — surfaces the top finding in plain language.
+        """
+        if not findings:
+            return AIInsight(
+                headline="No significant patterns detected in this run.",
+                diagnosis=(
+                    f"The EA completed {metrics.total_trades} trades with a profit factor of "
+                    f"{metrics.profit_factor:.2f} and {metrics.win_rate*100:.0f}% win rate. "
+                    "No statistically significant failure patterns were identified."
+                ),
+                patterns=[],
+                suggestions=[],
+                confidence="low",
+                risk_flags=["AI reasoning unavailable — set ANTHROPIC_API_KEY for full analysis"],
+            )
+
+        top = findings[0]
+        second = findings[1] if len(findings) > 1 else None
+
+        patterns = [f.description[:120] for f in findings[:3]]
+        suggestions = []
+        for f in findings[:2]:
+            for param, val in (f.suggested_params or {}).items():
+                suggestions.append({
+                    "param":  param,
+                    "from":   "current",
+                    "to":     val,
+                    "reason": f"Suggested by {f.analyzer} analyzer (confidence {f.confidence:.2f})"
+                })
+
+        risk_flags = ["AI reasoning running in fallback mode — set ANTHROPIC_API_KEY for full Opus analysis"]
+        if metrics.total_trades < 100:
+            risk_flags.append(f"Low trade count ({metrics.total_trades}) — statistical confidence is limited")
+        if metrics.max_drawdown_pct > 0.25:
+            risk_flags.append(f"High drawdown ({metrics.max_drawdown_pct*100:.0f}%) — risk parameters need review")
+
+        headline = f"{top.severity.upper()} issue: {top.description[:60]}..."
+        diagnosis = (
+            f"Primary issue ({top.analyzer}): {top.description} "
+            f"Estimated impact: ${top.impact_estimate_pnl:.0f}. "
+        )
+        if second:
+            diagnosis += f"Secondary issue ({second.analyzer}): {second.description[:100]}."
+
+        return AIInsight(
+            headline=headline,
+            diagnosis=diagnosis,
+            patterns=patterns,
+            suggestions=suggestions[:3],
+            confidence="medium" if findings and findings[0].confidence > 0.7 else "low",
+            risk_flags=risk_flags,
+        )
diff --git a/analysis/ai_reasoner_config.py b/analysis/ai_reasoner_config.py
new file mode 100644
index 0000000..d0dc59e
--- /dev/null
+++ b/analysis/ai_reasoner_config.py
@@ -0,0 +1,46 @@
+"""
+analysis/ai_reasoner_config.py
+Loads the Anthropic API key from config.yaml or environment.
+Add this to config.yaml:
+
+  ai:
+    anthropic_api_key: "sk-ant-..."
+    enabled: true
+"""
+from __future__ import annotations
+import os
+from pathlib import Path
+import yaml
+
+
+def load_api_key(config_path: str | Path = "config.yaml") -> str:
+    """
+    Load the Anthropic API key. Priority:
+    1. ANTHROPIC_API_KEY environment variable
+    2. config.yaml ai.anthropic_api_key
+    3. Empty string (fallback mode)
+    """
+    env_key = os.environ.get("ANTHROPIC_API_KEY", "")
+    if env_key:
+        return env_key
+
+    try:
+        with open(config_path) as f:
+            cfg = yaml.safe_load(f)
+        return cfg.get("ai", {}).get("anthropic_api_key", "")
+    except Exception:
+        return ""
+
+
+def is_ai_enabled(config_path: str | Path = "config.yaml") -> bool:
+    """Check if AI reasoning is enabled in config."""
+    env_key = os.environ.get("ANTHROPIC_API_KEY", "")
+    if env_key:
+        return True
+    try:
+        with open(config_path) as f:
+            cfg = yaml.safe_load(f)
+        ai_cfg = cfg.get("ai", {})
+        return ai_cfg.get("enabled", False) and bool(ai_cfg.get("anthropic_api_key", ""))
+    except Exception:
+        return False
diff --git a/app.py b/app.py
index 67a19b6..cb2a61a 100644
--- a/app.py
+++ b/app.py
@@ -124,17 +124,28 @@ def stop():
 
 @app.route("/api/history")
 def history():
-    """Score history for chart — built from pipeline results."""
+    """Full run history for chart/table restoration — includes in-progress runs."""
     if pipeline is None:
         return jsonify([])
+    if hasattr(pipeline, '_completed_runs') and pipeline._completed_runs:
+        # Sort newest first by timestamp (ts field added in _make_run_dict)
+        runs = sorted(pipeline._completed_runs,
+                      key=lambda r: r.get("ts", ""), reverse=True)
+        return jsonify(runs)
+    # Fallback: post-phase ranked results
     results = pipeline.phase1_results + pipeline.phase2_results
     return jsonify([
         {
-            "run_id":   r.run_id,
-            "score":    round(r.score, 4),
-            "calmar":   round(r.calmar, 3),
-            "passing":  r.passing,
-            "phase":    r.phase,
+            "run_id":        r.run_id,
+            "score":         round(r.score, 4),
+            "net_profit":    round(r.net_profit, 2),
+            "calmar":        round(r.calmar, 3),
+            "profit_factor": round(r.profit_factor, 3),
+            "max_drawdown":  round(r.max_drawdown, 2),
+            "total_trades":  r.total_trades,
+            "win_rate":      round(r.win_rate, 1),
+            "passing":       r.passing,
+            "phase":         r.phase,
         }
         for r in results
     ])
@@ -203,7 +214,7 @@ def runs_list():
     import json, re
     runs = []
     if REPORTS_DIR.exists():
-        for run_dir in sorted(REPORTS_DIR.iterdir(), reverse=True):
+        for run_dir in REPORTS_DIR.iterdir():
             if not run_dir.is_dir():
                 continue
             summary = run_dir / "summary.json"
@@ -218,9 +229,108 @@ def runs_list():
                     runs.append(data)
                 except Exception:
                     pass
+    # Sort by timestamp field (newest first)
+    runs.sort(key=lambda r: r.get("ts", ""), reverse=True)
     return jsonify(runs[:50])
 
 
+@app.route("/api/run/<run_id>")
+def run_detail(run_id):
+    """Return full detail for one run: metrics + params + AI insight + .set link."""
+    import json, re
+
+    run_dir = REPORTS_DIR / run_id
+    if not run_dir.exists():
+        return jsonify({"error": "Run not found"}), 404
+
+    def read_json(path):
+        try:
+            txt = path.read_text(encoding="utf-8")
+            txt = re.sub(r'\bNaN\b', 'null', txt)
+            txt = re.sub(r'\bInfinity\b', 'null', txt)
+            return json.loads(txt)
+        except Exception:
+            return None
+
+    summary    = read_json(run_dir / "summary.json") or {}
+    params     = read_json(run_dir / "parameters.json") or {}
+    ai_insight = read_json(run_dir / "ai_insight.json")
+
+    # Also check live pipeline for AI insight (current session, not yet on disk)
+    if ai_insight is None and pipeline and hasattr(pipeline, '_run_insights'):
+        ai_insight = pipeline._run_insights.get(run_id)
+
+    # Detect .set file
+    set_files = list(run_dir.glob("*.set"))
+    set_url   = f"/download_set/{run_id}" if set_files else None
+
+    return jsonify({
+        **summary,
+        "params":     params,
+        "ai_insight": ai_insight,
+        "set_url":    set_url,
+        "has_set":    bool(set_files),
+    })
+
+
+@app.route("/api/best_result")
+def best_result():
+    """
+    Return the current best run plus its evolution path — the ordered sequence
+    of AI iterations that led to it (so the user can see how the AI arrived).
+    """
+    if not pipeline:
+        return jsonify({"error": "No best result yet — optimization has not started."}), 404
+
+    best_run = None
+    if getattr(pipeline, "final_result", None):
+        best_run = pipeline.final_result
+    elif getattr(pipeline, "_live_best", None):
+        best_run = pipeline._live_best
+    if best_run is None:
+        return jsonify({"error": "No best result yet — no passing run found so far."}), 404
+
+    # Build evolution path: walk through _completed_runs up to (and including) the best
+    evolution = []
+    for r in getattr(pipeline, "_completed_runs", []):
+        phase = r.get("phase", "")
+        if not (phase.startswith("phase1") or phase.startswith("phase2")):
+            continue
+        ai_insight = r.get("ai_insight") or {}
+        evolution.append({
+            "run_id":        r.get("run_id"),
+            "phase":         phase,
+            "ts":            r.get("ts"),
+            "score":         r.get("score"),
+            "net_profit":    r.get("net_profit"),
+            "profit_factor": r.get("profit_factor"),
+            "calmar":        r.get("calmar"),
+            "max_drawdown":  r.get("max_drawdown"),
+            "passing":       r.get("passing"),
+            "changes":       ai_insight.get("changes") or [],
+            "analysis":      ai_insight.get("analysis") or ai_insight.get("diagnosis") or "",
+            "is_best":       r.get("run_id") == best_run.run_id,
+        })
+        if r.get("run_id") == best_run.run_id:
+            break
+
+    return jsonify({
+        "run_id":         best_run.run_id,
+        "score":          round(best_run.score, 4),
+        "net_profit":     round(best_run.net_profit, 2),
+        "profit_factor":  round(best_run.profit_factor, 3),
+        "calmar":         round(best_run.calmar, 3),
+        "max_drawdown":   round(best_run.max_drawdown, 2),
+        "win_rate":       round(best_run.win_rate, 1),
+        "total_trades":   best_run.total_trades,
+        "passing":        best_run.passing,
+        "phase":          getattr(best_run, "phase", "phase2_ai"),
+        "params":         best_run.params,
+        "evolution":      evolution,
+        "set_url":        f"/download_set/{best_run.run_id}",
+    })
+
+
 # ── SocketIO ──────────────────────────────────────────────────────────────────
 
 @socketio.on("connect")
@@ -229,6 +339,220 @@ def on_connect():
         emit("status_sync", pipeline.get_status())
 
 
+@app.route("/api/ai_insight/latest")
+def ai_insight_latest():
+    """Return the latest AI insight from the running pipeline."""
+    if pipeline and hasattr(pipeline, 'get_latest_insight'):
+        insight = pipeline.get_latest_insight()
+        if insight:
+            return jsonify(insight)
+    return jsonify(None)
+
+
+@app.route("/api/ai_insights")
+def ai_insights_all():
+    """Return all AI insights from this session."""
+    if pipeline and hasattr(pipeline, 'get_all_insights'):
+        return jsonify(pipeline.get_all_insights())
+    return jsonify([])
+
+
+@app.route("/api/settings", methods=["GET"])
+def get_settings():
+    import yaml
+    config_path = BASE_DIR / "config.yaml"
+    try:
+        with open(config_path, encoding="utf-8") as f:
+            cfg = yaml.safe_load(f) or {}
+        ai_cfg = cfg.get("ai", {})
+        mt5_cfg = cfg.get("mt5", {})
+        broker_cfg = cfg.get("broker", {})
+        thresh_cfg = cfg.get("thresholds", {})
+        return jsonify({
+            "ai": {
+                "enabled":          ai_cfg.get("enabled", True),
+                "anthropic_api_key": ai_cfg.get("anthropic_api_key", ""),
+                "model":            ai_cfg.get("model", "claude-opus-4-7"),
+                "timeout_seconds":  ai_cfg.get("timeout_seconds", 30),
+            },
+            "mt5": {
+                "terminal_exe":          mt5_cfg.get("terminal_exe", ""),
+                "appdata_path":          mt5_cfg.get("appdata_path", ""),
+                "mql5_files_path":       mt5_cfg.get("mql5_files_path", ""),
+                "tester_timeout_seconds": mt5_cfg.get("tester_timeout_seconds", 120),
+                "tester_model":          mt5_cfg.get("tester_model", 1),
+            },
+            "broker": {
+                "timezone_offset_hours": broker_cfg.get("timezone_offset_hours", 3),
+                "deposit":              broker_cfg.get("deposit", 10000),
+                "leverage":             broker_cfg.get("leverage", 500),
+            },
+            "thresholds": {
+                "min_trades":            thresh_cfg.get("min_trades", 30),
+                "min_profit_factor":     thresh_cfg.get("min_profit_factor", 1.2),
+                "min_calmar":            thresh_cfg.get("min_calmar", 0.5),
+                "max_oos_degradation":   thresh_cfg.get("max_oos_degradation", 0.3),
+                "sensitivity_tolerance": thresh_cfg.get("sensitivity_tolerance", 0.15),
+            },
+        })
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+
+@app.route("/api/settings", methods=["POST"])
+def save_settings():
+    import yaml
+    config_path = BASE_DIR / "config.yaml"
+    data = request.get_json(silent=True) or {}
+    try:
+        with open(config_path, encoding="utf-8") as f:
+            cfg = yaml.safe_load(f) or {}
+        for section in ["ai", "mt5", "broker", "thresholds"]:
+            if section in data and isinstance(data[section], dict):
+                if section not in cfg:
+                    cfg[section] = {}
+                cfg[section].update(data[section])
+        with open(config_path, "w", encoding="utf-8") as f:
+            yaml.dump(cfg, f, default_flow_style=False, allow_unicode=True)
+        return jsonify({"ok": True})
+    except Exception as e:
+        return jsonify({"ok": False, "error": str(e)}), 500
+
+
+@app.route("/api/ea/register", methods=["POST"])
+def ea_register():
+    """Register a new EA profile."""
+    from ea.registry import EARegistry, EAProfile
+    data = request.get_json(silent=True) or {}
+    try:
+        reg = EARegistry(str(BASE_DIR / "config.yaml"))
+        profile = EAProfile(
+            name=data["name"],
+            ex5_file=data.get("ex5_file", data["name"]),
+            set_template=data["set_template"],
+            symbol=data.get("symbol", "XAUUSD"),
+            timeframe=data.get("timeframe", "H1"),
+            mode=data.get("mode", "generic"),
+        )
+        reg.register(profile)
+        return jsonify({"ok": True, "name": profile.name})
+    except Exception as e:
+        return jsonify({"ok": False, "error": str(e)}), 400
+
+
+@app.route("/api/ea/list")
+def ea_list():
+    """List all registered EAs."""
+    from ea.registry import EARegistry
+    try:
+        reg = EARegistry(str(BASE_DIR / "config.yaml"))
+        profiles = reg.list_all()
+        return jsonify([{
+            "name": p.name,
+            "symbol": p.symbol,
+            "timeframe": p.timeframe,
+            "mode": p.mode,
+            "set_template": p.set_template,
+        } for p in profiles])
+    except Exception as e:
+        return jsonify([])
+
+
+@app.route("/ai_insights")
+def ai_insights_page():
+    """Legacy alias — AI insights now live inline on the dashboard."""
+    return redirect("/dashboard")
+
+
+@app.route("/api/ea/scan")
+def ea_scan():
+    """Scan common MT5 locations for .ex5 and .set files."""
+    import glob as _glob
+    import os
+
+    home = Path(os.path.expanduser("~"))
+    appdata = Path(os.environ.get("APPDATA", home / "AppData" / "Roaming"))
+    desktop = home / "Desktop"
+
+    # Directories to scan for .ex5 files — MetaQuotes terminal data dirs
+    ex5_dirs = []
+    mq_base = appdata / "MetaQuotes" / "Terminal"
+    if mq_base.exists():
+        for td in mq_base.iterdir():
+            if td.is_dir():
+                ex5_dirs.append(td / "MQL5" / "Experts")
+    ex5_dirs.append(Path("C:/Program Files/MetaTrader 5/MQL5/Experts"))
+    ex5_dirs.append(Path("C:/Program Files (x86)/MetaTrader 5/MQL5/Experts"))
+
+    # Scan .ex5 files (skip Examples / Advisors / Free Robots subfolders — likely default)
+    SKIP_DIRS = {"Examples", "Advisors", "Free Robots", "Market"}
+    ex5_found = []
+    seen_names = set()
+    for d in ex5_dirs:
+        if not d.exists():
+            continue
+        for f in d.rglob("*.ex5"):
+            if any(part in SKIP_DIRS for part in f.parts):
+                continue
+            name = f.stem
+            if name not in seen_names:
+                seen_names.add(name)
+                ex5_found.append({
+                    "name": name,
+                    "path": str(f).replace("\\", "/"),
+                    "dir": str(f.parent).replace("\\", "/"),
+                })
+
+    # Scan .set files — Desktop, Desktop subfolders, MT5 tester agents
+    set_dirs = [desktop]
+    # Desktop subfolders (1 level deep)
+    for item in desktop.iterdir() if desktop.exists() else []:
+        if item.is_dir():
+            set_dirs.append(item)
+    # MT5 tester agent MQL5/Files
+    tester_base = appdata / "MetaQuotes" / "Tester"
+    if tester_base.exists():
+        for td in tester_base.rglob("MQL5/Files"):
+            set_dirs.append(td)
+
+    set_found = []
+    seen_set = set()
+    for d in set_dirs:
+        if not d.exists():
+            continue
+        for f in d.glob("*.set"):
+            key = f.name
+            if key not in seen_set:
+                seen_set.add(key)
+                set_found.append({
+                    "name": f.stem,
+                    "filename": f.name,
+                    "path": str(f).replace("\\", "/"),
+                })
+
+    # Build best-match hints: for each ex5, find the most likely .set file
+    def best_set_for(ea_name):
+        ea_lower = ea_name.lower()
+        # exact match first
+        for s in set_found:
+            if s["name"].lower() == ea_lower:
+                return s["path"]
+        # prefix/suffix match
+        for s in set_found:
+            sl = s["name"].lower()
+            if ea_lower in sl or sl in ea_lower:
+                return s["path"]
+        return ""
+
+    for ea in ex5_found:
+        ea["suggested_set"] = best_set_for(ea["name"])
+
+    return jsonify({
+        "ex5": ex5_found,
+        "set": set_found,
+    })
+
+
 # ── Launch ────────────────────────────────────────────────────────────────────
 
 def open_browser():
@@ -242,4 +566,4 @@ if __name__ == "__main__":
     print("  Opening browser at http://localhost:5000")
     print("=" * 60)
     threading.Thread(target=open_browser, daemon=True).start()
-    socketio.run(app, host="0.0.0.0", port=5000, debug=False, use_reloader=False)
+    socketio.run(app, host="0.0.0.0", port=5000, debug=False, use_reloader=False, allow_unsafe_werkzeug=True)
diff --git a/config.example.yaml b/config.example.yaml
new file mode 100644
index 0000000..43b8423
--- /dev/null
+++ b/config.example.yaml
@@ -0,0 +1,122 @@
+# ── APEX MT5 Optimizer — example config ─────────────────────────────────────
+# Copy this file to `config.yaml` and fill in your values. config.yaml is
+# git-ignored so your secrets stay local.
+#
+#   cp config.example.yaml config.yaml
+#
+# Or set ANTHROPIC_API_KEY as an environment variable and the app will pick it
+# up automatically (overrides whatever is in config.yaml).
+
+ai:
+  enabled: true
+  # Get your key from https://console.anthropic.com/
+  # Leave as-is to use the ANTHROPIC_API_KEY environment variable.
+  anthropic_api_key: ${ANTHROPIC_API_KEY}
+  model: claude-opus-4-7              # claude-opus-4-7 | claude-sonnet-4-6 | claude-haiku-4-5
+  timeout_seconds: 45
+  analyze_every_n_iterations: 1
+
+# ── Strategy thresholds — quality gates a result must clear ────────────────
+thresholds:
+  min_trades: 50
+  min_profit_factor: 1.2
+  min_calmar: 0.35
+  min_wfv_ratio: 0.7
+  max_oos_degradation: 0.3
+  sensitivity_tolerance: 0.3
+
+# ── Scoring weights — how the ranker combines metrics ──────────────────────
+scoring:
+  significance_trades: 150
+  weights:
+    calmar:           0.35
+    profit_factor:    0.20
+    mfe_capture:      0.20
+    session_stability: 0.15
+    recovery_factor:  0.10
+  normalization:
+    calmar:           { lo: 0.0, hi: 4.0 }
+    profit_factor:    { lo: 1.0, hi: 3.5 }
+    recovery_factor:  { lo: 0.0, hi: 6.0 }
+    mfe_capture:      { lo: 0.0, hi: 1.0 }
+    session_stability: { lo: 0.0, hi: 1.0 }
+
+# ── Broker / market context ────────────────────────────────────────────────
+broker:
+  currency: USD
+  deposit:  10000
+  leverage: 100
+  timezone_offset_hours: 2
+  sessions:
+    Asian:    { start: 0,  end: 9  }
+    London:   { start: 9,  end: 18 }
+    LondonNY: { start: 15, end: 18 }
+    NY:       { start: 15, end: 24 }
+
+# ── EA selection (auto-populated when you register an EA in /setup) ────────
+ea:
+  name:      LEGSTECH_EA_V2
+  file:      LEGSTECH_EA_V2
+  symbol:    XAUUSD
+  timeframe: H1
+
+# ── MetaTrader 5 paths ─────────────────────────────────────────────────────
+# Adjust these to match your local MT5 installation.
+mt5:
+  terminal_exe:  C:/Program Files/MetaTrader 5/terminal64.exe
+  appdata_path:  C:/Users/<YOU>/AppData/Roaming/MetaQuotes/Terminal/<HASH>
+  mql5_files_path: C:/Users/<YOU>/AppData/Roaming/MetaQuotes/Tester/<HASH>/Agent-127.0.0.1-3000/MQL5/Files
+  report_subdir: runs
+  tester_model:  4              # 1=Every tick, 2=Real ticks, 3=OHLC, 4=Open prices
+  tester_timeout_seconds: 1800
+  data_readiness_wait_seconds: 10
+  kill_on_start:    true
+  shutdown_terminal: 1
+
+# ── Backtest periods ───────────────────────────────────────────────────────
+periods:
+  train_start:    2022.01.01
+  train_end:      2023.12.31
+  validate_start: 2024.01.01
+  validate_end:   2024.06.30
+  oos_start:      2024.07.01
+  oos_end:        2024.12.31
+
+# ── Optimization tuning ────────────────────────────────────────────────────
+optimization:
+  max_iterations:        50
+  convergence_threshold: 0.04
+  convergence_window:    3
+
+mutation:
+  max_hypotheses_per_cycle: 3
+  dedup_lookback_runs:      10
+  explore_fallback_after:   5
+
+analysis:
+  equity_curve:
+    min_r_squared:      0.7
+    max_flatness_score: 0.5
+  reversal:
+    mfe_threshold_pips: 15.0
+    min_reversal_rate:  0.15
+    permutation_n:      500
+  time_performance:
+    min_trades_per_bucket: 10
+    permutation_n:         1000
+    z_score_threshold:     -1.5
+  entry_exit:
+    poor_entry_quality: 0.4
+    poor_exit_quality:  0.55
+
+# ── Paths ──────────────────────────────────────────────────────────────────
+paths:
+  db:           optimizer.db
+  reports_dir:  reports
+  runs_dir:     runs
+  ea_registry:  ea_registry.yaml
+  log_file:     optimizer.log
+
+logging:
+  level: INFO
+  file:  optimizer.log
diff --git a/config.yaml b/config.yaml
deleted file mode 100644
index c43ca34..0000000
--- a/config.yaml
+++ /dev/null
@@ -1,104 +0,0 @@
-# MT5 EA Strategy Optimizer — Master Configuration
-# EA identity is managed in ea_registry.yaml (source of truth for new code).
-# The ea: block below is kept as a bridge for legacy code paths.
-# ─────────────────────────────────────────────
-
-ea:
-  name: "LEGSTECH_EA_V2"
-  file: "LEGSTECH_EA_V2"
-  symbol: "XAUUSD"
-  timeframe: "H1"
-
-periods:
-  train_start: "2022.01.01"
-  train_end:   "2023.12.31"
-  validate_start: "2024.01.01"
-  validate_end:   "2024.06.30"
-  oos_start:   "2024.07.01"        # LOCKED — never touched during optimization
-  oos_end:     "2024.12.31"
-
-broker:
-  timezone_offset_hours: 2         # Broker server = UTC+2. Set to 0 for UTC brokers.
-  deposit: 10000.0
-  currency: "USD"
-  leverage: 100
-  # Session definitions in BROKER LOCAL TIME (will be normalized to UTC internally)
-  sessions:
-    Asian:    {start: 0,  end: 9}
-    London:   {start: 9,  end: 18}   # UTC+2: 07:00 UTC = 09:00 broker
-    NY:       {start: 15, end: 24}   # UTC+2: 13:00 UTC = 15:00 broker
-    LondonNY: {start: 15, end: 18}   # Overlap
-
-mt5:
-  terminal_exe: "C:/Program Files/MetaTrader 5/terminal64.exe"
-  # Terminal data folder — detected automatically from your MetaQuotes installation
-  appdata_path: "C:/Users/DELL/AppData/Roaming/MetaQuotes/Terminal/D0E8209F77C8CF37AD8BF550E51FF075"
-  # MQL5 Files folder — TradeLogger CSV is written here during backtests
-  # NOTE: Strategy Tester writes to the Agent subfolder, not the terminal Files folder
-  mql5_files_path: "C:/Users/DELL/AppData/Roaming/MetaQuotes/Tester/D0E8209F77C8CF37AD8BF550E51FF075/Agent-127.0.0.1-3000/MQL5/Files"
-  tester_model: 4                   # 4=OHLC M1 (fast, reliable). Use 0=Every Tick only if full tick data available
-  tester_timeout_seconds: 1800      # 30 min max per test
-  shutdown_terminal: 1              # ShutdownTerminal=1 in INI — MT5 closes after test
-  data_readiness_wait_seconds: 10   # Wait N seconds after MT5 launch for data to load before testing
-  kill_on_start: true               # Always kill existing MT5 before each run
-  report_subdir: "runs"             # relative to project root
-
-logging:
-  level: "INFO"                     # DEBUG | INFO | WARNING | ERROR
-  file: "optimizer.log"
-
-thresholds:
-  min_trades: 50                    # below this → no statistical confidence
-  min_profit_factor: 1.20
-  min_calmar: 0.35
-  max_oos_degradation: 0.30         # 30% drop IS→OOS is acceptable; above = reject
-  sensitivity_tolerance: 0.30       # ±10% param → >30% calmar drop = fragile, reject
-  min_wfv_ratio: 0.70               # OOS calmar must be ≥ 70% of IS calmar in WFV
-
-scoring:
-  weights:
-    calmar:            0.35
-    profit_factor:     0.20
-    mfe_capture:       0.20         # avg MFE capture ratio (exit quality)
-    session_stability: 0.15         # 1 - std_dev of per-session Calmar
-    recovery_factor:   0.10
-  normalization:
-    calmar:            {lo: 0.0, hi: 4.0}
-    profit_factor:     {lo: 1.0, hi: 3.5}
-    mfe_capture:       {lo: 0.0, hi: 1.0}
-    session_stability: {lo: 0.0, hi: 1.0}
-    recovery_factor:   {lo: 0.0, hi: 6.0}
-  significance_trades: 150          # full significance weight at this trade count
-
-analysis:
-  reversal:
-    mfe_threshold_pips: 15.0        # minimum MFE to classify as reversal candidate
-    min_reversal_rate:  0.15        # above this → HIGH finding
-    permutation_n:      500         # permutation tests for significance
-  time_performance:
-    min_trades_per_bucket: 10       # ignore time buckets with fewer trades
-    z_score_threshold: -1.5         # flag as negative edge
-    permutation_n: 1000
-  entry_exit:
-    poor_exit_quality:  0.55        # below this → HIGH finding
-    poor_entry_quality: 0.40        # below this → HIGH finding
-  equity_curve:
-    max_flatness_score: 0.50        # above this → raise finding
-    min_r_squared:      0.70        # below this → high variance
-
-mutation:
-  max_hypotheses_per_cycle: 3       # test at most N hypotheses before picking best
-  dedup_lookback_runs: 10           # avoid re-testing same delta seen in last N runs
-  explore_fallback_after: 5         # switch to explore if N targeted runs all rejected
-
-optimization:
-  max_iterations: 50
-  convergence_window: 3             # stop if no improvement in this many promotions
-  convergence_threshold: 0.04       # minimum composite score delta to count as improvement
-
-paths:
-  db: "optimizer.db"
-  runs_dir: "runs"
-  reports_dir: "reports"
-  log_file: "optimizer.log"
-  ea_registry: "ea_registry.yaml"   # EA profiles (symbol, .set path, mode)
diff --git a/demo/__init__.py b/demo/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/demo/run_demo.py b/demo/run_demo.py
new file mode 100644
index 0000000..a32f29f
--- /dev/null
+++ b/demo/run_demo.py
@@ -0,0 +1,142 @@
+"""
+demo/run_demo.py
+APEX offline demo runner.
+
+Spins up the Flask + SocketIO app with APEX_DEMO_MODE=1 so the optimizer
+generates synthetic backtest results instead of calling MT5. Lets judges
+without a Windows + MT5 install see the full live AI loop, validation,
+and verdict flow.
+
+Usage:
+    python -m demo.run_demo
+    # or
+    python demo/run_demo.py
+"""
+from __future__ import annotations
+
+import os
+import sys
+import textwrap
+from pathlib import Path
+
+import yaml
+
+ROOT      = Path(__file__).resolve().parent.parent
+DEMO_DIR  = Path(__file__).resolve().parent
+DEMO_SET  = DEMO_DIR / "demo_ea.set"
+REGISTRY  = ROOT / "ea_registry.yaml"
+CONFIG    = ROOT / "config.yaml"
+EXAMPLE_CONFIG = ROOT / "config.example.yaml"
+
+DEMO_PROFILE = {
+    "name":         "APEX_DEMO_EA",
+    "ex5_file":     "APEX_DEMO_EA",
+    "set_template": str(DEMO_SET).replace("\\", "/"),
+    "symbol":       "XAUUSD",
+    "timeframe":    "H1",
+    "mode":         "advanced",
+    "registered_at": "2026-01-01T00:00:00+00:00",
+    "optimize_params": {
+        "InpRiskPercent":     True,
+        "InpMaxDailyLossPct": True,
+        "InpRRRatio":         True,
+        "InpStopLossPips":    True,
+        "InpTakeProfitPips":  True,
+        "InpATRMultiplier":   True,
+        "InpUseTrailing":     True,
+        "InpTrailStartPips":  True,
+        "InpUseBreakeven":    True,
+        "InpBEPips":          True,
+        "InpMinScore":        True,
+    },
+    "automation_overrides": {},
+}
+
+
+def ensure_demo_registry() -> None:
+    """Make sure the demo EA profile exists in ea_registry.yaml."""
+    if REGISTRY.exists():
+        try:
+            data = yaml.safe_load(REGISTRY.read_text()) or {"profiles": []}
+        except Exception:
+            data = {"profiles": []}
+    else:
+        data = {"profiles": []}
+
+    profiles = data.get("profiles") or []
+    if not any(p.get("name") == DEMO_PROFILE["name"] for p in profiles):
+        profiles.append(DEMO_PROFILE)
+        data["profiles"] = profiles
+        REGISTRY.write_text(yaml.safe_dump(data, sort_keys=False))
+        print(f"  [ok] Registered demo EA in {REGISTRY.name}")
+    else:
+        print(f"  [ok] Demo EA already in {REGISTRY.name}")
+
+
+def ensure_config() -> None:
+    """If config.yaml is missing, copy config.example.yaml as a starting point."""
+    if not CONFIG.exists():
+        if EXAMPLE_CONFIG.exists():
+            CONFIG.write_text(EXAMPLE_CONFIG.read_text())
+            print(f"  [ok] Created {CONFIG.name} from template")
+        else:
+            print(f"  [!] No config.yaml or config.example.yaml — app may fail to start")
+
+
+def banner() -> None:
+    bar = "=" * 72
+    print(textwrap.dedent(f"""
+        {bar}
+                          APEX -- DEMO MODE (offline / no MT5)
+        {bar}
+          * Backtests are synthetic (deterministic from params + jitter)
+          * The AI loop, validation, and verdict flow are 100% real
+          * Set ANTHROPIC_API_KEY to see live AI reasoning
+
+          Open http://localhost:5000 in your browser, hit "New Run", and
+          watch the AI think.
+        {bar}
+    """))
+
+
+def main() -> int:
+    banner()
+
+    print("Bootstrapping demo environment...")
+    ensure_config()
+    ensure_demo_registry()
+
+    # Set the demo flag — the pipeline checks this in _execute_run.
+    os.environ["APEX_DEMO_MODE"] = "1"
+    # Per-run latency tunable — keep small so demo feels snappy.
+    os.environ.setdefault("APEX_DEMO_RUN_SECONDS", "1.2")
+
+    if "ANTHROPIC_API_KEY" not in os.environ:
+        print("  [!] ANTHROPIC_API_KEY not set — AI reasoning will be skipped (synthetic metrics still flow).")
+
+    print()
+    print("Launching APEX server at http://localhost:5000 ...")
+    sys.path.insert(0, str(ROOT))
+    # Import after env vars are set so the pipeline picks them up.
+    import threading
+    import webbrowser
+    from app import app as flask_app, socketio
+
+    def _open_browser():
+        import time as _t
+        _t.sleep(1.5)
+        try:
+            webbrowser.open("http://localhost:5000")
+        except Exception:
+            pass
+
+    threading.Thread(target=_open_browser, daemon=True).start()
+    socketio.run(
+        flask_app, host="0.0.0.0", port=5000,
+        debug=False, use_reloader=False, allow_unsafe_werkzeug=True,
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/ea_registry.yaml b/ea_registry.yaml
deleted file mode 100644
index c4ac7b7..0000000
--- a/ea_registry.yaml
+++ /dev/null
@@ -1,35 +0,0 @@
-profiles:
-- name: LEGSTECH_EA_V2
-  ex5_file: LEGSTECH_EA_V2
-  set_template: C:/Users/DELL/Desktop/MT5 Set files/LEGSTECH_EA_V2.set
-  symbol: XAUUSD
-  timeframe: H1
-  mode: advanced
-  registered_at: '2026-04-13T19:52:30.824439+00:00'
-  optimize_params:
-    InpRiskPercent: true
-    InpMaxDailyLossPct: true
-    InpMaxTradesPerDay: true
-    InpRRRatio: true
-    InpUseTrailing: true
-    InpTrailStartPips: true
-    InpTrailStepPips: true
-    InpUseBreakeven: true
-    InpBEPips: true
-    InpBEBufferPips: true
-    InpUseSession: true
-    InpSessionStart: true
-    InpSessionEnd: true
-    InpMinScore: true
-    InpATRMultiplier: true
-    InpBotMode: false
-    InpRiskType: false
-    InpSLType: false
-    InpSLBuffer: false
-    InpFixedSLPips: false
-    InpUseSpreadGuard: true
-    InpMaxSpreadPips: true
-  automation_overrides:
-    InpShowPanel: 0
-    InpTesterMode: 1
-    InpTesterInitDeposit: 10000.0
diff --git a/optimizer/ai_guided_loop.py b/optimizer/ai_guided_loop.py
new file mode 100644
index 0000000..bcffd90
--- /dev/null
+++ b/optimizer/ai_guided_loop.py
@@ -0,0 +1,576 @@
+"""
+optimizer/ai_guided_loop.py
+AI-Guided Autonomous Optimization Loop.
+
+Replaces Phase 2's blind random neighbor search with directed,
+AI-driven parameter evolution. Each iteration:
+
+  1. Build rich context: parameter schema + full history
+  2. Ask AI: "what parameter values should I try next?"
+  3. Apply changes with bounds checking
+  4. Deduplicate (don't re-test seen param sets)
+  5. Run backtest via existing pipeline._execute_run()
+  6. Check stop conditions (targets met OR max iterations)
+  7. Emit progress to frontend, update pipeline state
+  8. Loop
+
+The loop terminates when:
+  - All quality targets are met by the current best result
+  - Max iterations reached
+  - Stop flag set externally (user clicked Stop)
+  - Budget exhausted
+"""
+from __future__ import annotations
+
+import hashlib
+import json
+import random
+import time
+from datetime import datetime
+from typing import Optional
+
+from loguru import logger
+
+from ea.schema import ParameterSchema
+from optimizer.result_ranker import RankedResult, ResultRanker
+from optimizer.session_config import SessionConfig
+from analysis.ai_reasoner import AIReasoner, AIParamSuggestion
+
+
+class AIGuidedLoop:
+    """
+    Autonomous AI-driven parameter search.
+
+    Usage (from inside OptimizationPipeline._run_pipeline):
+        loop = AIGuidedLoop(pipeline, schema, cfg, builder, runner,
+                            parser, store, writer, ranker, profile, budget)
+        loop.run(seed_results, max_iterations, targets)
+        # Results available in loop.all_results, loop.best_result
+    """
+
+    # If last N iterations show less than this score improvement → escape
+    STUCK_WINDOW    = 3
+    STUCK_THRESHOLD = 0.005
+
+    def __init__(
+        self,
+        pipeline,           # OptimizationPipeline — for _execute_run / _emit / _log
+        schema: ParameterSchema,
+        cfg: SessionConfig,
+        builder, runner, parser, store, writer,
+        ranker: ResultRanker,
+        profile,
+        budget,
+    ):
+        self.pipeline = pipeline
+        self.schema   = schema
+        self.cfg      = cfg
+        self.builder  = builder
+        self.runner   = runner
+        self.parser   = parser
+        self.store    = store
+        self.writer   = writer
+        self.ranker   = ranker
+        self.profile  = profile
+        self.budget   = budget
+
+        # Public results — populated during run()
+        self.all_results:  list[RankedResult] = []
+        self.best_result:  Optional[RankedResult] = None
+
+        # Internal state
+        self._iteration_history: list[dict] = []  # rich history for AI prompt
+        self._seen_hashes:       set[str]   = set()
+        self._rng = random.Random(int(time.time()))
+
+    # ── Public entry point ────────────────────────────────────────────────────
+
+    def run(
+        self,
+        seed_results: list[RankedResult],
+        max_iterations: int,
+        targets: dict,
+    ) -> RankedResult:
+        """
+        Run the autonomous loop. Returns the best result found.
+
+        seed_results:   Phase 1 ranked results (provides initial best + seen params)
+        max_iterations: hard cap on AI-directed iterations
+        targets:        {min_profit_factor, max_drawdown_pct, min_calmar}
+        """
+        self._initialize_from_seeds(seed_results)
+
+        self._log("info", f"━━ AI-Guided Loop: up to {max_iterations} iterations ━━")
+        self._log("info",
+            f"   Targets → PF≥{targets.get('min_profit_factor',1.5)} | "
+            f"DD≤{targets.get('max_drawdown_pct',20)}% | "
+            f"Calmar≥{targets.get('min_calmar',0.5)}"
+        )
+        self._think(
+            f"Targets set — PF≥{targets.get('min_profit_factor',1.5)}, "
+            f"DD≤{targets.get('max_drawdown_pct',20)}%, Calmar≥{targets.get('min_calmar',0.5)}. "
+            f"I'll stop as soon as I hit them, or after {max_iterations} iterations.",
+            kind="reasoning",
+        )
+
+        schema_info = self._build_schema_info()
+
+        for iteration in range(1, max_iterations + 1):
+            if self.pipeline._stop_flag:
+                self._log("info", "Loop stopped by user.")
+                break
+
+            if self.budget.is_exhausted():
+                self._log("warning", "⏱ Time budget exhausted — stopping AI loop.")
+                break
+
+            # Check if current best already satisfies all targets
+            if self.best_result and self._targets_met(self.best_result, targets):
+                self._log("info",
+                    f"✅ All targets met after iteration {iteration - 1}! "
+                    f"PF={self.best_result.profit_factor:.2f}, "
+                    f"DD={self.best_result.max_drawdown:.1f}%, "
+                    f"Calmar={self.best_result.calmar:.2f}"
+                )
+                self._think(
+                    f"All quality targets reached after iteration {iteration - 1}. "
+                    f"Best config: PF={self.best_result.profit_factor:.2f}, "
+                    f"DD={self.best_result.max_drawdown:.1f}%, "
+                    f"Calmar={self.best_result.calmar:.2f}. Stopping early — no need to keep iterating.",
+                    kind="success",
+                )
+                self._emit("ai_targets_met", {
+                    "iteration": iteration - 1,
+                    "profit_factor": round(self.best_result.profit_factor, 3),
+                    "max_drawdown":  round(self.best_result.max_drawdown, 2),
+                    "calmar":        round(self.best_result.calmar, 3),
+                })
+                self.pipeline._emit_early_termination(
+                    reason_code="targets_met",
+                    message=f"All targets met at iteration {iteration - 1}. Optimization complete.",
+                    details={
+                        "iteration":     iteration - 1,
+                        "profit_factor": round(self.best_result.profit_factor, 3),
+                        "max_drawdown":  round(self.best_result.max_drawdown, 2),
+                        "calmar":        round(self.best_result.calmar, 3),
+                    },
+                )
+                break
+
+            self._log("info",
+                f"[AI Loop {iteration}/{max_iterations}] "
+                f"Best so far: PF={self.best_result.profit_factor:.2f}, "
+                f"Calmar={self.best_result.calmar:.2f}, "
+                f"DD={self.best_result.max_drawdown:.1f}%"
+                if self.best_result else f"[AI Loop {iteration}/{max_iterations}] Starting..."
+            )
+            self._think(
+                f"Iteration {iteration}: reviewing history and deciding what to change next...",
+                kind="info", iteration=iteration,
+            )
+
+            # Get AI suggestion for next params
+            suggestion = self._get_suggestion(schema_info, targets)
+
+            # Surface the AI's reasoning as its own thinking message
+            if suggestion.analysis:
+                self._think(suggestion.analysis, kind="reasoning", iteration=iteration)
+
+            # Apply changes to best params → candidate param set
+            base_params = self.best_result.params if self.best_result else self.schema.defaults()
+            next_params = self._apply_changes(
+                base=base_params,
+                changes=suggestion.changes,
+            )
+
+            # Escape if stuck or AI returned no changes
+            is_stuck = self._check_stuck()
+            if is_stuck or not suggestion.changes:
+                if is_stuck:
+                    self._log("warning", f"  ⚠ Stuck detected — applying random escape at iteration {iteration}")
+                    self._think(
+                        f"Recent scores are flat — the AI is stuck in a local optimum. "
+                        f"Applying a random ±30% perturbation to escape and explore a new region.",
+                        kind="warning", iteration=iteration,
+                    )
+                else:
+                    self._log("warning", f"  ⚠ AI returned no changes — applying random escape")
+                    self._think(
+                        "AI returned no changes — falling back to a random perturbation so we keep exploring.",
+                        kind="warning", iteration=iteration,
+                    )
+                next_params = self._random_escape(next_params)
+                self._emit("ai_stuck", {"iteration": iteration})
+
+            # Deduplicate — ensure we're not re-testing an identical config
+            next_params = self._ensure_unique(next_params, max_attempts=5)
+
+            # Build rich param change records (prev → new + reason) for the UI
+            change_records = self._build_change_records(base_params, next_params, suggestion.changes)
+
+            # Narrate the actual parameter changes
+            for c in change_records[:4]:  # cap noise
+                self._think(
+                    f"{c['param']}: {c['from']} → {c['to']} — {c['reason']}",
+                    kind="decision",
+                    iteration=iteration,
+                    meta=c,
+                )
+
+            # Emit iteration start
+            self._emit("ai_iteration_start", {
+                "iteration":       iteration,
+                "max_iterations":  max_iterations,
+                "analysis":        suggestion.analysis,
+                "changes":         suggestion.changes,
+                "change_records":  change_records,
+                "confidence":      round(suggestion.confidence, 2),
+                "is_stuck_escape": is_stuck or not suggestion.changes,
+            })
+
+            # Dedicated richer event that the dashboard subscribes to
+            self._emit("param_changes", {
+                "iteration":  iteration,
+                "run_id":     None,  # filled in after run below via complete event
+                "analysis":   suggestion.analysis,
+                "changes":    change_records,
+                "confidence": round(suggestion.confidence, 2),
+            })
+
+            # Run the backtest
+            run_id = f"ai_{iteration:02d}_{datetime.utcnow().strftime('%H%M%S')}"
+            t0     = time.time()
+            result = self.pipeline._execute_run(
+                run_id, next_params,
+                self.cfg.train_start, self.cfg.train_end,
+                "phase2_ai",
+                self.builder, self.runner, self.parser,
+                self.store, self.writer, self.ranker, self.profile,
+            )
+            elapsed = time.time() - t0
+            self.budget.record_run(elapsed)
+
+            # Register result
+            self.all_results.append(result)
+            self._mark_seen(next_params)
+            self._update_best(result)
+            self.pipeline._run_count += 1
+
+            # Update pipeline live state
+            if (self.pipeline._live_best is None
+                    or result.score > self.pipeline._live_best.score):
+                self.pipeline._live_best = result
+
+            run_dict = self.pipeline._make_run_dict(run_id, result, "phase2_ai")
+            self.pipeline._completed_runs.append(run_dict)
+
+            # Record iteration for AI history
+            targets_met = self.best_result and self._targets_met(self.best_result, targets)
+            self._record_iteration(iteration, run_id, result, suggestion)
+
+            goal_status = {
+                "profit_factor_met": result.profit_factor >= targets.get("min_profit_factor", 1.5),
+                "drawdown_ok":       result.max_drawdown  <= targets.get("max_drawdown_pct",   20.0),
+                "calmar_met":        result.calmar        >= targets.get("min_calmar",           0.5),
+            }
+
+            # Narrate the outcome of this iteration
+            improved = (self.best_result is self.all_results[-1]) if self.all_results else False
+            if result.passing and improved:
+                self._think(
+                    f"✓ Iteration {iteration} improved the best score to {result.score:.3f} "
+                    f"(PF={result.profit_factor:.2f}, Calmar={result.calmar:.2f}, "
+                    f"DD={result.max_drawdown:.1f}%). Keeping these params as the new baseline.",
+                    kind="success", iteration=iteration,
+                )
+            elif result.passing:
+                self._think(
+                    f"Iteration {iteration} passed thresholds but didn't beat the best — "
+                    f"score {result.score:.3f} vs best {self.best_result.score:.3f}.",
+                    kind="info", iteration=iteration,
+                )
+            else:
+                diagnosis = self._diagnose_failure(result, targets)
+                self._think(
+                    f"✗ Iteration {iteration} failed: {diagnosis} "
+                    f"(PF={result.profit_factor:.2f}, DD={result.max_drawdown:.1f}%). "
+                    f"Will adjust in the next step.",
+                    kind="warning", iteration=iteration,
+                )
+
+            # Emit iteration complete
+            self._emit("ai_iteration_complete", {
+                "iteration":       iteration,
+                "max_iterations":  max_iterations,
+                "run_id":          run_id,
+                "score":           round(result.score, 4),
+                "profit_factor":   round(result.profit_factor, 3),
+                "calmar":          round(result.calmar, 3),
+                "max_drawdown":    round(result.max_drawdown, 2),
+                "net_profit":      round(result.net_profit, 2),
+                "total_trades":    result.total_trades,
+                "passing":         result.passing,
+                "best_score":      round(self.best_result.score, 4) if self.best_result else 0,
+                "best_pf":         round(self.best_result.profit_factor, 3) if self.best_result else 0,
+                "best_calmar":     round(self.best_result.calmar, 3) if self.best_result else 0,
+                "goal_status":     goal_status,
+                "targets_met":     bool(targets_met),
+                "improved":        bool(improved),
+                "confidence":      round(suggestion.confidence, 2),
+                "analysis":        suggestion.analysis,
+                "change_records":  change_records,
+            })
+
+            self._emit("run_complete", {
+                "run_id":        run_id,
+                "phase":         "phase2_ai",
+                "net_profit":    round(result.net_profit, 2),
+                "calmar":        round(result.calmar, 3),
+                "profit_factor": round(result.profit_factor, 3),
+                "win_rate":      round(result.win_rate, 1),
+                "max_drawdown":  round(result.max_drawdown, 2),
+                "total_trades":  result.total_trades,
+                "passing":       result.passing,
+                "score":         round(result.score, 4),
+                "progress_pct":  round(self.pipeline._run_count / max(self.pipeline._total_runs, 1) * 100),
+            })
+
+            status = "✅" if result.passing else "❌"
+            self._log(
+                "info" if result.passing else "warning",
+                f"  {status} iter={iteration} | PF={result.profit_factor:.2f} | "
+                f"Calmar={result.calmar:.2f} | DD={result.max_drawdown:.1f}% | "
+                f"trades={result.total_trades} | confidence={suggestion.confidence:.2f}"
+            )
+
+        return self.best_result
+
+    # ── Initialization ────────────────────────────────────────────────────────
+
+    def _initialize_from_seeds(self, seed_results: list[RankedResult]) -> None:
+        """Register Phase 1 results as seen and find initial best."""
+        for r in seed_results:
+            self._mark_seen(r.params)
+
+        passing = [r for r in seed_results if r.passing]
+        if passing:
+            self.best_result = max(passing, key=lambda r: r.score)
+            self._log("info",
+                f"AI loop seed: best Phase 1 result is {self.best_result.run_id} "
+                f"(PF={self.best_result.profit_factor:.2f}, score={self.best_result.score:.4f})"
+            )
+
+        # Populate initial iteration history from Phase 1 top results
+        top_seeds = sorted(passing, key=lambda r: r.score, reverse=True)[:5]
+        for i, r in enumerate(top_seeds):
+            self._iteration_history.append({
+                "iteration":    f"p1_top{i+1}",
+                "run_id":       r.run_id,
+                "score":        round(r.score, 4),
+                "pf":           round(r.profit_factor, 3),
+                "calmar":       round(r.calmar, 3),
+                "dd":           round(r.max_drawdown, 2),
+                "trades":       r.total_trades,
+                "changes":      [],  # LHS seeds have no "changes"
+                "params":       r.params,
+            })
+
+    # ── AI interaction ────────────────────────────────────────────────────────
+
+    def _get_suggestion(
+        self, schema_info: list[dict], targets: dict
+    ) -> AIParamSuggestion:
+        """Ask AIReasoner for the next parameter set."""
+        reasoner: AIReasoner = self.pipeline._ai_reasoner
+        if not reasoner or not reasoner.enabled:
+            return AIParamSuggestion(
+                analysis="AI unavailable — using random escape.",
+                changes=[], confidence=0.0, goal_status={}, error="no_ai",
+            )
+
+        current_params = self.best_result.params if self.best_result else self.schema.defaults()
+
+        return reasoner.suggest_next_params(
+            current_best_params=current_params,
+            schema_info=schema_info,
+            iteration_history=self._iteration_history,
+            targets=targets,
+        )
+
+    # ── Parameter manipulation ────────────────────────────────────────────────
+
+    def _build_schema_info(self) -> list[dict]:
+        """Convert schema optimizable params to serializable dicts for the AI prompt."""
+        return [
+            {
+                "name":    p.name,
+                "type":    p.type,
+                "min":     p.min,
+                "max":     p.max,
+                "step":    p.step,
+                "default": p.default,
+                "enum_values": p.enum_values if p.type == "enum" else [],
+            }
+            for p in self.schema.optimizable()
+        ]
+
+    def _apply_changes(self, base: dict, changes: list[dict]) -> dict:
+        """
+        Apply AI-suggested changes to base params.
+        Uses ParameterDef.clamp() to enforce valid ranges and types.
+        """
+        result = dict(base)
+        param_map = {p.name: p for p in self.schema.optimizable()}
+
+        for change in changes:
+            name  = change.get("param", "")
+            value = change.get("value")
+            if name not in param_map or value is None:
+                continue
+            pdef = param_map[name]
+            try:
+                result[name] = pdef.clamp(float(value) if pdef.type in ("float", "int") else value)
+            except Exception as e:
+                logger.debug(f"AIGuidedLoop: skipping change {name}={value}: {e}")
+
+        return result
+
+    def _build_change_records(
+        self, before: dict, after: dict, ai_changes: list[dict]
+    ) -> list[dict]:
+        """
+        Produce a list of {param, from, to, reason} records for the UI.
+
+        The AI's suggested changes may include a `reason` per change; we match
+        those by name. Parameters that differ without a matching reason still
+        get recorded (labelled "random perturbation").
+        """
+        reason_by_param = {
+            c.get("param"): c.get("reason", "").strip()
+            for c in (ai_changes or [])
+            if c.get("param")
+        }
+        records = []
+        for name, new_val in after.items():
+            old_val = before.get(name)
+            if old_val == new_val:
+                continue
+            records.append({
+                "param":  name,
+                "from":   old_val,
+                "to":     new_val,
+                "reason": reason_by_param.get(name) or "random perturbation (escape from stuck region)",
+            })
+        return records
+
+    def _random_escape(self, base: dict) -> dict:
+        """Random perturbation when stuck — perturbs 2-4 random optimizable params by ±30% of range."""
+        opts = self.schema.optimizable()
+        if not opts:
+            return dict(base)
+
+        candidate = dict(base)
+        n_perturb = min(len(opts), self._rng.randint(2, 4))
+        to_perturb = self._rng.sample(opts, n_perturb)
+
+        for p in to_perturb:
+            if p.type == "bool":
+                candidate[p.name] = not candidate.get(p.name, p.default)
+            elif p.type == "enum":
+                candidate[p.name] = self._rng.choice(p.enum_values)
+            else:
+                span  = float(p.max) - float(p.min)
+                delta = span * 0.30 * self._rng.choice([-1, 1])
+                candidate[p.name] = p.clamp(float(candidate.get(p.name, p.default)) + delta)
+
+        return candidate
+
+    def _ensure_unique(self, params: dict, max_attempts: int = 5) -> dict:
+        """If params already seen, perturb until unique (or give up)."""
+        for _ in range(max_attempts):
+            if self._hash(params) not in self._seen_hashes:
+                return params
+            params = self._random_escape(params)
+        return params  # best effort
+
+    def _mark_seen(self, params: dict) -> None:
+        self._seen_hashes.add(self._hash(params))
+
+    @staticmethod
+    def _hash(params: dict) -> str:
+        key = json.dumps(params, sort_keys=True, default=str)
+        return hashlib.md5(key.encode()).hexdigest()
+
+    # ── Best tracking ─────────────────────────────────────────────────────────
+
+    def _update_best(self, result: RankedResult) -> None:
+        if result.passing:
+            if self.best_result is None or result.score > self.best_result.score:
+                self.best_result = result
+
+    # ── Stop conditions ───────────────────────────────────────────────────────
+
+    def _diagnose_failure(self, result: RankedResult, targets: dict) -> str:
+        """Human-readable reason this iteration didn't pass quality gates."""
+        reasons = []
+        if result.max_drawdown > targets.get("max_drawdown_pct", 20.0):
+            reasons.append(f"drawdown too high ({result.max_drawdown:.1f}%)")
+        if result.profit_factor < targets.get("min_profit_factor", 1.5):
+            reasons.append(f"profit factor too low ({result.profit_factor:.2f})")
+        if result.calmar < targets.get("min_calmar", 0.5):
+            reasons.append(f"Calmar too low ({result.calmar:.2f})")
+        if result.net_profit <= 0:
+            reasons.append(f"unprofitable (${result.net_profit:.0f})")
+        if result.total_trades < 10:
+            reasons.append(f"too few trades ({result.total_trades})")
+        return ", ".join(reasons) or "result below quality threshold"
+
+    def _targets_met(self, result: RankedResult, targets: dict) -> bool:
+        if not result or not result.passing:
+            return False
+        return (
+            result.profit_factor >= targets.get("min_profit_factor", 1.5)
+            and result.max_drawdown  <= targets.get("max_drawdown_pct",   20.0)
+            and result.calmar        >= targets.get("min_calmar",           0.5)
+        )
+
+    def _check_stuck(self) -> bool:
+        """Return True if last STUCK_WINDOW iterations improved less than STUCK_THRESHOLD."""
+        ai_iters = [h for h in self._iteration_history if str(h.get("iteration", "")).startswith(("1","2","3","4","5","6","7","8","9"))]
+        if len(ai_iters) < self.STUCK_WINDOW:
+            return False
+        recent_scores = [h["score"] for h in ai_iters[-self.STUCK_WINDOW:]]
+        return (max(recent_scores) - min(recent_scores)) < self.STUCK_THRESHOLD
+
+    # ── History tracking ──────────────────────────────────────────────────────
+
+    def _record_iteration(
+        self,
+        iteration: int,
+        run_id: str,
+        result: RankedResult,
+        suggestion: AIParamSuggestion,
+    ) -> None:
+        self._iteration_history.append({
+            "iteration": iteration,
+            "run_id":    run_id,
+            "score":     round(result.score, 4),
+            "pf":        round(result.profit_factor, 3),
+            "calmar":    round(result.calmar, 3),
+            "dd":        round(result.max_drawdown, 2),
+            "trades":    result.total_trades,
+            "changes":   suggestion.changes,
+            "params":    result.params,
+        })
+
+    # ── Pipeline helpers ──────────────────────────────────────────────────────
+
+    def _emit(self, event: str, data: dict = {}) -> None:
+        self.pipeline._emit(event, data)
+
+    def _log(self, level: str, msg: str) -> None:
+        self.pipeline._log(level, msg)
+
+    def _think(self, msg: str, kind: str = "info", iteration: Optional[int] = None, meta: Optional[dict] = None) -> None:
+        """Stream an AI-thinking message to the dashboard."""
+        self.pipeline._emit_thinking(msg, kind=kind, iteration=iteration, meta=meta)
diff --git a/optimizer/pipeline.py b/optimizer/pipeline.py
index ce74c3f..c790794 100644
--- a/optimizer/pipeline.py
+++ b/optimizer/pipeline.py
@@ -13,17 +13,18 @@ Architecture:
 """
 from __future__ import annotations
 
+import hashlib
+import os
+import random
 import time
-import uuid
-import threading
 from datetime import datetime
 from pathlib import Path
-from typing import Any, Optional, Callable
+from typing import Optional
 
 import yaml
 from loguru import logger
 
-from ea.registry import EARegistry, EAProfile
+from ea.registry import EARegistry
 from ea.schema import ParameterSchema
 from mt5.ini_builder import IniBuilder
 from mt5.runner import MT5Runner
@@ -39,6 +40,11 @@ from optimizer.budget import BudgetManager
 
 import pandas as pd
 
+from analysis.equity_curve import EquityCurveAnalyzer
+from analysis.time_performance import TimePerformanceAnalyzer
+from analysis.ai_reasoner import AIReasoner
+from analysis.ai_reasoner_config import load_api_key
+
 BASE_DIR  = Path(__file__).parent.parent
 RUNS_DIR  = BASE_DIR / "runs"
 DB_PATH   = BASE_DIR / "optimizer.db"
@@ -78,6 +84,18 @@ class OptimizationPipeline:
         self.best_set_path: Optional[Path] = None
         self.run_start_ts: Optional[float] = None
 
+        # AI & analysis state
+        self._ai_reasoner: Optional[AIReasoner] = None
+        self._ai_insights: list[dict] = []
+        self._run_findings: dict[str, list] = {}
+        self._run_insights: dict[str, dict] = {}
+        self._baseline_metrics: Optional[dict] = None
+
+        # Running best (updated each run so status can serve it live)
+        self._live_best: Optional[RankedResult] = None
+        # All completed runs (for history restoration)
+        self._completed_runs: list[dict] = []
+
     # ── Public API ────────────────────────────────────────────────────────────
 
     def configure(self, session: SessionConfig) -> None:
@@ -86,20 +104,36 @@ class OptimizationPipeline:
     def stop(self) -> None:
         self._stop_flag = True
         self._emit("status_change", {"state": "stopping"})
+        self._emit_early_termination(
+            reason_code="user_stop",
+            message="User requested stop. Finishing current run and exiting.",
+            details={"phase": self._phase},
+        )
 
     def get_status(self) -> dict:
         elapsed = int(time.time() - self.run_start_ts) if self.run_start_ts else 0
+        # Use final_result if set, otherwise best seen so far during the run
+        best = self.final_result or self._live_best
         return {
             "state":         "running" if self.running else "idle",
             "phase":         self._phase,
             "run_count":     self._run_count,
             "total_runs":    self._total_runs,
-            "best_score":    round(self.best_result.score, 4) if self.best_result else 0.0,
+            "best_score":    round(best.score, 4) if best else 0.0,
             "verdict":       self.verdict,
             "elapsed_s":     elapsed,
             "ea_name":       self.session.ea_name if self.session else "",
             "symbol":        self.session.symbol if self.session else "",
             "timeframe":     self.session.timeframe if self.session else "",
+            "has_insight":        bool(self._ai_insights),
+            "insight_count":      len(self._ai_insights),
+            "latest_insight":     self._ai_insights[-1] if self._ai_insights else None,
+            "best_net_profit":    round(best.net_profit, 2) if best else None,
+            "best_calmar":        round(best.calmar, 3) if best else None,
+            "best_pf":            round(best.profit_factor, 3) if best else None,
+            "best_win_rate":      round(best.win_rate, 1) if best else None,
+            "best_max_drawdown":  round(best.max_drawdown, 2) if best else None,
+            "best_total_trades":  best.total_trades if best else None,
         }
 
     # ── Main entry point ──────────────────────────────────────────────────────
@@ -147,6 +181,13 @@ class OptimizationPipeline:
         ranker   = ResultRanker(weights=cfg.scoring_weights)
         budget   = BudgetManager(cfg.budget_minutes)
 
+        # Initialize AI reasoning layer
+        api_key = load_api_key(self.config_path)
+        self._ai_reasoner = AIReasoner(api_key=api_key)
+        self._ai_insights.clear()
+        self._run_findings.clear()
+        self._run_insights.clear()
+
         budget.start()
 
         # ── Phase 1: Broad Discovery ─────────────────────────────────────────
@@ -155,6 +196,11 @@ class OptimizationPipeline:
 
         self._phase = "phase1"
         self._emit("phase_start", {"phase": "phase1", "total": cfg.phase1_samples})
+        self._emit_thinking(
+            f"Starting broad discovery with {cfg.phase1_samples} Latin-Hypercube samples. "
+            f"Scanning parameter space to find profitable regions before focused refinement.",
+            kind="reasoning",
+        )
         self._log("info", f"━━ Phase 1: Broad Discovery ({cfg.phase1_samples} configurations) ━━")
 
         samples = sampler.sample(schema, cfg.phase1_samples)
@@ -176,19 +222,17 @@ class OptimizationPipeline:
             phase1_raw.append(result)
             self._run_count += 1
 
+            # Track live best and completed runs for status/history APIs
+            if self._live_best is None or result.score > self._live_best.score:
+                self._live_best = result
+            run_dict = self._make_run_dict(run_id, result, "phase1")
+            self._completed_runs.append(run_dict)
+
             # Emit progress after each run
             self._emit("run_complete", {
-                "run_id":         run_id,
-                "phase":          "phase1",
+                **run_dict,
                 "run_number":     i + 1,
                 "total":          cfg.phase1_samples,
-                "net_profit":     round(result.net_profit, 2),
-                "calmar":         round(result.calmar, 3),
-                "profit_factor":  round(result.profit_factor, 3),
-                "win_rate":       round(result.win_rate, 1),
-                "max_drawdown":   round(result.max_drawdown, 2),
-                "total_trades":   result.total_trades,
-                "passing":        result.passing,
                 "progress_pct":   round((i + 1) / cfg.phase1_samples * 100),
                 "budget_summary": budget.summary(),
             })
@@ -221,19 +265,101 @@ class OptimizationPipeline:
                     "or try a different timeframe."
                 )
             })
+            self._emit_early_termination(
+                reason_code="no_profit",
+                message="Optimization stopped early: Phase 1 found no profitable configuration.",
+                details={
+                    "phase": "phase1",
+                    "total_tested": len(self.phase1_results),
+                    "suggestions": [
+                        "Try a different date range",
+                        "Check EA settings for issues",
+                        "Try a different timeframe",
+                    ],
+                },
+            )
+            self._emit_thinking(
+                "No profitable configuration found across the broad scan. "
+                "Strategy is unstable under current EA settings — stopping optimization.",
+                kind="warning",
+            )
             self._log("error", "❌ No profitable configuration found in Phase 1. Stopping.")
             return
 
         if self._stop_flag:
             return
 
-        # ── Phase 2: Deep Refinement ─────────────────────────────────────────
+        # ── Phase 2: Refinement (AI-Guided or Random Neighbor) ───────────────
         if not budget.can_fit(3):
             self._log("warning", "⏱ Not enough budget for Phase 2 — using Phase 1 winner directly")
             self.final_result = top5[0]
+
+        elif cfg.autonomous_mode and self._ai_reasoner and self._ai_reasoner.enabled:
+            # ── AI-Guided Autonomous Loop ─────────────────────────────────────
+            self._phase = "phase2"
+            self._emit("phase_start", {
+                "phase": "phase2",
+                "total": cfg.autonomous_max_iterations,
+                "mode":  "autonomous",
+            })
+            self._emit_thinking(
+                f"Phase 1 found {len(top5)} promising candidates. Best Calmar is "
+                f"{top5[0].calmar:.2f}. Switching to autonomous AI loop — I'll read each "
+                f"result, decide what parameters to change, and iterate toward the targets.",
+                kind="reasoning",
+            )
+            self._log("info",
+                f"━━ Phase 2: Autonomous AI Loop "
+                f"(up to {cfg.autonomous_max_iterations} iterations) ━━"
+            )
+
+            from optimizer.ai_guided_loop import AIGuidedLoop
+            loop = AIGuidedLoop(
+                pipeline=self, schema=schema, cfg=cfg,
+                builder=builder, runner=runner, parser=parser,
+                store=store, writer=writer, ranker=ranker,
+                profile=profile, budget=budget,
+            )
+            targets = {
+                "min_profit_factor": cfg.target_profit_factor,
+                "max_drawdown_pct":  cfg.target_max_drawdown_pct,
+                "min_calmar":        cfg.target_min_calmar,
+            }
+            loop.run(
+                seed_results=self.phase1_results,
+                max_iterations=cfg.autonomous_max_iterations,
+                targets=targets,
+            )
+
+            self.phase2_results = loop.all_results
+            all_candidates = [r for r in (self.phase1_results + loop.all_results) if r.passing]
+            all_ranked     = ranker.rank(all_candidates) if all_candidates else ranker.rank(self.phase1_results)
+            self.final_result = all_ranked[0] if all_ranked else top5[0]
+
+            self._emit("phase2_complete", {
+                "best_run_id":   self.final_result.run_id,
+                "best_score":    round(self.final_result.score, 4),
+                "best_profit":   round(self.final_result.net_profit, 2),
+                "best_calmar":   round(self.final_result.calmar, 3),
+                "mode":          "autonomous",
+                "iterations":    len(loop.all_results),
+            })
+            self._log("info",
+                f"AI Loop complete. Best: {self.final_result.run_id} "
+                f"(PF={self.final_result.profit_factor:.2f}, "
+                f"profit=${self.final_result.net_profit:.0f}, "
+                f"calmar={self.final_result.calmar:.2f})"
+            )
+
         else:
+            # ── Original Random-Neighbor Phase 2 ─────────────────────────────
             self._phase = "phase2"
             self._emit("phase_start", {"phase": "phase2", "total": cfg.phase2_samples})
+            self._emit_thinking(
+                f"Phase 2 starting in classic mode: sampling {cfg.phase2_samples} neighbors "
+                f"around the top {min(3, len(top5))} Phase-1 winners (no AI loop).",
+                kind="info",
+            )
             self._log("info", f"━━ Phase 2: Deep Refinement (refining top {min(3, len(top5))} configs) ━━")
 
             top3        = top5[:3]
@@ -264,20 +390,19 @@ class OptimizationPipeline:
                     phase2_raw.append(result)
                     self._run_count += 1
 
+                    run_dict_p2 = self._make_run_dict(run_id, result, "phase2")
+                    self._completed_runs.append(run_dict_p2)
+                    if self._live_best is None or result.score > self._live_best.score:
+                        self._live_best = result
                     self._emit("run_complete", {
-                        "run_id":     run_id,
-                        "phase":      "phase2",
-                        "net_profit": round(result.net_profit, 2),
-                        "calmar":     round(result.calmar, 3),
-                        "passing":    result.passing,
+                        **run_dict_p2,
                         "progress_pct": round(self._run_count / self._total_runs * 100),
                     })
 
-            # Best from Phase 1 + Phase 2 combined
             all_results = list(self.phase1_results) + ranker.rank(phase2_raw)
             all_ranked  = ranker.rank(
                 [r for r in all_results if r.passing]
-                or list(self.phase1_results)  # fallback to Phase 1 if P2 all fail
+                or list(self.phase1_results)
             )
             self.phase2_results = ranker.rank(phase2_raw)
             self.final_result   = all_ranked[0] if all_ranked else top5[0]
@@ -299,16 +424,56 @@ class OptimizationPipeline:
         # ── Phase 3: Validation ───────────────────────────────────────────────
         if not budget.can_fit(2):
             self._log("warning", "⏱ Not enough budget for Phase 3 validation — skipping OOS test")
+            self._emit_early_termination(
+                reason_code="budget_exhausted",
+                message="Skipping validation: not enough time budget remaining.",
+                details={"phase": "phase3"},
+            )
             self.verdict = "RISKY"
             oos_result = None
         else:
             self._phase = "phase3"
             self._emit("phase_start", {"phase": "phase3", "total": cfg.phase3_samples})
+
+            # Count the validation runs we intend to run so progress makes sense
+            opts          = schema.optimizable()
+            plan_sens     = bool(opts) and budget.can_fit(2)
+            planned_runs  = 1 + (2 if plan_sens else 0)  # 1 OOS + 2 sens
+            self._emit("validation_start", {
+                "best_run_id":     self.final_result.run_id,
+                "planned_runs":    planned_runs,
+                "oos_start":       cfg.val_start,
+                "oos_end":         cfg.val_end,
+                "train_start":     cfg.train_start,
+                "train_end":       cfg.train_end,
+                "sensitivity":     plan_sens,
+            })
+            self._emit_thinking(
+                f"Entering validation phase. Testing best config {self.final_result.run_id} "
+                f"on out-of-sample data ({cfg.val_start} → {cfg.val_end}) + sensitivity checks.",
+                kind="reasoning",
+            )
             self._log("info", "━━ Phase 3: Validation (out-of-sample + sensitivity) ━━")
 
-            # OOS test
+            # ── OOS test ──
             oos_id = f"oos_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}"
             self._log("info", f"  OOS test: {cfg.val_start} → {cfg.val_end}")
+            self._emit("validation_run_start", {
+                "run_id":      oos_id,
+                "kind":        "oos",
+                "label":       "Out-of-Sample",
+                "description": f"Re-testing best config on unseen data: {cfg.val_start} → {cfg.val_end}",
+                "index":       1,
+                "total":       planned_runs,
+                "period_start": cfg.val_start,
+                "period_end":   cfg.val_end,
+                "params":       self.final_result.params,
+            })
+            self._emit_thinking(
+                "Running out-of-sample test: if the strategy holds up on data it wasn't "
+                "optimized on, the edge is real — not curve-fit noise.",
+                kind="hypothesis",
+            )
             t0 = time.time()
             oos_result = self._execute_run(
                 oos_id, self.final_result.params,
@@ -318,20 +483,47 @@ class OptimizationPipeline:
             budget.record_run(time.time() - t0)
             self._run_count += 1
 
-            self._emit("run_complete", {
-                "run_id":     oos_id,
-                "phase":      "phase3_oos",
-                "net_profit": round(oos_result.net_profit, 2),
-                "calmar":     round(oos_result.calmar, 3),
-                "passing":    oos_result.passing,
+            oos_dict = self._make_run_dict(oos_id, oos_result, "phase3_oos")
+            self._completed_runs.append(oos_dict)
+            self._emit("run_complete", {**oos_dict, "progress_pct": round(self._run_count / self._total_runs * 100)})
+            self._emit("validation_run_complete", {
+                "run_id":        oos_id,
+                "kind":          "oos",
+                "label":         "Out-of-Sample",
+                "index":         1,
+                "total":         planned_runs,
+                "net_profit":    round(oos_result.net_profit, 2),
+                "profit_factor": round(oos_result.profit_factor, 3),
+                "calmar":        round(oos_result.calmar, 3),
+                "max_drawdown":  round(oos_result.max_drawdown, 2),
+                "total_trades":  oos_result.total_trades,
+                "passing":       oos_result.passing,
             })
+            # Thinking narration on OOS outcome
+            oos_ratio = (oos_result.calmar / max(self.final_result.calmar, 0.001)) if oos_result.calmar else 0
+            if oos_result.net_profit > 0 and oos_ratio >= 0.50:
+                self._emit_thinking(
+                    f"OOS profitable: ${oos_result.net_profit:.0f} with Calmar {oos_result.calmar:.2f} "
+                    f"(≈{oos_ratio*100:.0f}% of training performance). The edge generalizes.",
+                    kind="success",
+                )
+            else:
+                self._emit_thinking(
+                    f"OOS weak: profit ${oos_result.net_profit:.0f}, Calmar {oos_result.calmar:.2f} — "
+                    f"strategy likely overfit to the training period.",
+                    kind="warning",
+                )
 
-            # Sensitivity test (2 runs: nudge top param up and down)
+            # ── Sensitivity test (2 runs: nudge top param up and down) ──
             sens_results = []
-            opts = schema.optimizable()
             if opts and budget.can_fit(2):
                 top_param = opts[0]  # first optimizable param
-                for direction in [1, -1]:
+                self._emit_thinking(
+                    f"Sensitivity check: nudging `{top_param.name}` ±20% to see if performance "
+                    f"survives small parameter drift.",
+                    kind="reasoning",
+                )
+                for i, direction in enumerate([1, -1], start=2):
                     if budget.is_exhausted() or self._stop_flag:
                         break
                     nudged = dict(self.final_result.params)
@@ -340,6 +532,19 @@ class OptimizationPipeline:
                     nudged[top_param.name] = top_param.clamp(current + direction * span * 0.20)
 
                     sens_id = f"sens_{direction}_{datetime.utcnow().strftime('%H%M%S')}"
+                    label   = f"Sensitivity ({top_param.name} {'+' if direction > 0 else '-'}20%)"
+                    self._emit("validation_run_start", {
+                        "run_id":      sens_id,
+                        "kind":        "sensitivity",
+                        "label":       label,
+                        "description": f"Nudging `{top_param.name}` to {nudged[top_param.name]} "
+                                       f"(from {current}) to test parameter stability.",
+                        "index":       i,
+                        "total":       planned_runs,
+                        "period_start": cfg.train_start,
+                        "period_end":   cfg.train_end,
+                        "params":       nudged,
+                    })
                     t0 = time.time()
                     sr = self._execute_run(
                         sens_id, nudged, cfg.train_start, cfg.train_end,
@@ -349,9 +554,44 @@ class OptimizationPipeline:
                     sens_results.append(sr)
                     self._run_count += 1
 
+                    sens_dict = self._make_run_dict(sens_id, sr, "phase3_sens")
+                    self._completed_runs.append(sens_dict)
+                    self._emit("run_complete", {**sens_dict, "progress_pct": round(self._run_count / max(self._total_runs, 1) * 100)})
+                    self._emit("validation_run_complete", {
+                        "run_id":        sens_id,
+                        "kind":          "sensitivity",
+                        "label":         label,
+                        "index":         i,
+                        "total":         planned_runs,
+                        "net_profit":    round(sr.net_profit, 2),
+                        "profit_factor": round(sr.profit_factor, 3),
+                        "calmar":        round(sr.calmar, 3),
+                        "max_drawdown":  round(sr.max_drawdown, 2),
+                        "total_trades":  sr.total_trades,
+                        "passing":       sr.passing,
+                    })
+
             # Determine verdict
             self.verdict = self._determine_verdict(self.final_result, oos_result, sens_results)
 
+            # Validation done — narrate the conclusion
+            self._emit("validation_done", {
+                "verdict":      self.verdict,
+                "oos_passing":  bool(oos_result and oos_result.passing),
+                "sens_passing": sum(1 for s in sens_results if s.passing),
+                "sens_total":   len(sens_results),
+            })
+            verdict_narration = {
+                "RECOMMENDED":  "Validation passed on all fronts. Strategy is robust and ready for deployment.",
+                "RISKY":        "Validation mixed. Strategy may work but has stability concerns — proceed with care.",
+                "NOT_RELIABLE": "Validation failed. Strategy is not reliable — likely overfit or unstable.",
+            }.get(self.verdict, "Validation complete.")
+            self._emit_thinking(
+                verdict_narration,
+                kind=("success" if self.verdict == "RECOMMENDED"
+                      else "warning" if self.verdict == "RISKY" else "warning"),
+            )
+
         # ── Generate .set output ─────────────────────────────────────────────
         self.best_set_path = self._write_set_file(self.final_result, schema, cfg)
 
@@ -359,6 +599,7 @@ class OptimizationPipeline:
         self._emit("optimization_complete", {
             "verdict":       self.verdict,
             "best_run_id":   self.final_result.run_id,
+            "score":         round(self.final_result.score, 4),
             "net_profit":    round(self.final_result.net_profit, 2),
             "calmar":        round(self.final_result.calmar, 3),
             "profit_factor": round(self.final_result.profit_factor, 3),
@@ -386,6 +627,11 @@ class OptimizationPipeline:
         builder, runner, parser, store, writer, ranker, profile
     ) -> RankedResult:
         """Execute one MT5 backtest and return a RankedResult."""
+        # Demo mode short-circuit — generate synthetic metrics so judges can see the
+        # AI loop without an MT5 install. Toggle with APEX_DEMO_MODE=1.
+        if os.environ.get("APEX_DEMO_MODE", "").strip() in ("1", "true", "yes"):
+            return self._execute_demo_run(run_id, params, phase, ranker)
+
         run_dir = RUNS_DIR / run_id
         run_dir.mkdir(parents=True, exist_ok=True)
 
@@ -420,20 +666,135 @@ class OptimizationPipeline:
                 return ranker.make_result(run_id, params, phase, None,
                                           error=result.error_message)
 
-            metrics, _ = parser.parse(result.report_xml, result.report_html)
+            metrics, trades = parser.parse(result.report_xml, result.report_html)
             if metrics is None:
                 return ranker.make_result(run_id, params, phase, None,
                                           error="parse_failed")
 
             metrics.run_id = run_id
-            writer.write(run_id, metrics, pd.DataFrame(), [], params)
 
-            return ranker.make_result(run_id, params, phase, metrics)
+            # Run analysis & AI reasoning
+            findings = self._analyze_run(run_id, metrics, trades or [], params)
+            self._reason_about_run(run_id, metrics, findings, params)
+
+            trades_df = pd.DataFrame()
+            if trades:
+                try:
+                    trades_df = pd.DataFrame([t.model_dump() for t in trades])
+                except Exception:
+                    try:
+                        trades_df = pd.DataFrame([vars(t) for t in trades])
+                    except Exception:
+                        pass
+
+            # Build RankedResult first so we have the ranked_score for summary.json
+            ranked = ranker.make_result(run_id, params, phase, metrics)
+
+            ai_insight = self._run_insights.get(run_id)
+            writer.write(
+                run_id, metrics, trades_df, findings, params,
+                phase=phase,
+                ranked_score=ranked.score,
+                ai_insight=ai_insight,
+            )
+
+            return ranked
 
         except Exception as e:
             logger.warning(f"[{run_id}] Run error: {e}")
             return ranker.make_result(run_id, params, phase, None, error=str(e))
 
+    # ── Demo mode (synthetic backtest) ────────────────────────────────────────
+
+    def _execute_demo_run(self, run_id: str, params: dict, phase: str, ranker) -> RankedResult:
+        """
+        Generate a synthetic, deterministic-but-realistic RankedResult from the
+        params hash. Lets the AI loop run end-to-end without MT5 installed.
+
+        The metrics improve as parameters approach a hidden "sweet spot" so the
+        AI can hill-climb in a way judges can observe. We also add small jitter
+        to look organic.
+        """
+        from data.models import RunMetrics  # local import to avoid cycle
+
+        # Hash params → stable seed per config
+        key = ",".join(f"{k}={v}" for k, v in sorted(params.items()))
+        seed = int(hashlib.md5(key.encode()).hexdigest()[:12], 16)
+        rng = random.Random(seed)
+
+        # Hidden sweet-spot hash drift: a deterministic "true score" between 0–1
+        # based on a smooth function of parameter values. Small param changes
+        # produce small score changes — that's what lets the AI hill-climb.
+        true_score = 0.0
+        for k, v in sorted(params.items()):
+            try:
+                fv = float(v)
+                # Map value into [-1,1] using a stable hash, multiply by a gentle
+                # bias toward "moderate" values (sweet spot is mid-range).
+                slot = (int(hashlib.md5(k.encode()).hexdigest()[:8], 16) % 100) / 100.0
+                normalized = (fv % 100) / 100.0
+                true_score += 1.0 - abs(normalized - slot)
+            except Exception:
+                true_score += 0.5
+        if params:
+            true_score /= len(params)
+        true_score = max(0.05, min(0.98, true_score))
+
+        # Add jitter for realism (±10%)
+        true_score *= rng.uniform(0.90, 1.10)
+        true_score = max(0.05, min(0.99, true_score))
+
+        # Project onto realistic metric ranges
+        profit_factor = round(0.7 + true_score * 1.8, 3)        # 0.7–2.5
+        calmar        = round(true_score * 1.4, 3)              # 0.0–1.4
+        max_drawdown  = round(28 - true_score * 22, 2)          # 28%→6%
+        win_rate      = round(40 + true_score * 25, 1)          # 40%→65%
+        total_trades  = int(80 + rng.random() * 220)            # 80–300
+        net_profit    = round((profit_factor - 1) * 5000 * (1 + rng.uniform(-0.2, 0.2)), 2)
+
+        # Out-of-sample tends to be slightly worse (more realistic)
+        if phase.startswith("phase3_oos"):
+            profit_factor *= 0.85
+            calmar        *= 0.80
+            net_profit    *= 0.75
+
+        avg_trade = net_profit / max(total_trades, 1)
+        winners = int(total_trades * (win_rate / 100.0))
+        losers  = max(1, total_trades - winners)
+        # Derive avg win/loss consistent with profit_factor: PF = (winners*avg_win)/(losers*|avg_loss|)
+        avg_loss = -abs(avg_trade) * (1 + 1.5 / max(profit_factor, 0.5))
+        avg_win  = (profit_factor * losers * abs(avg_loss)) / max(winners, 1)
+
+        metrics = RunMetrics(
+            run_id=run_id,
+            net_profit=net_profit,
+            profit_factor=profit_factor,
+            calmar_ratio=calmar,
+            max_drawdown_pct=max_drawdown / 100.0,
+            max_drawdown_abs=round(net_profit * (max_drawdown / 100.0) * 1.2 + 200, 2),
+            win_rate=win_rate / 100.0,
+            total_trades=total_trades,
+            recovery_factor=round(profit_factor * 1.5, 2),
+            sharpe_ratio=round(true_score * 1.8, 2),
+            avg_win=round(avg_win, 2),
+            avg_loss=round(avg_loss, 2),
+            largest_loss=round(avg_loss * 3.5, 2),
+            expected_payoff=round(avg_trade, 2),
+        )
+
+        # Simulate per-run latency so the dashboard feels alive — not instant.
+        # Each run takes ~1.5s so a 10-iteration AI loop is ~15s total.
+        delay = float(os.environ.get("APEX_DEMO_RUN_SECONDS", "1.5"))
+        time.sleep(max(0.05, delay))
+
+        # Run AI reasoning if enabled — same flow as live mode
+        try:
+            self._reason_about_run(run_id, metrics, [], params)
+        except Exception:
+            pass
+
+        return ranker.make_result(run_id, params, phase, metrics)
+
     # ── Verdict logic ─────────────────────────────────────────────────────────
 
     def _determine_verdict(
@@ -501,37 +862,173 @@ class OptimizationPipeline:
 
     # ── Helpers ───────────────────────────────────────────────────────────────
 
+    def _make_run_dict(self, run_id: str, result: RankedResult, phase: str) -> dict:
+        """Canonical run dict used for both _completed_runs and run_complete emits."""
+        d = {
+            "run_id":        run_id,
+            "phase":         phase,
+            "ts":            datetime.utcnow().isoformat(),
+            "net_profit":    round(result.net_profit, 2),
+            "calmar":        round(result.calmar, 3),
+            "profit_factor": round(result.profit_factor, 3),
+            "win_rate":      round(result.win_rate, 1),
+            "max_drawdown":  round(result.max_drawdown, 2),
+            "total_trades":  result.total_trades,
+            "passing":       result.passing,
+            "score":         round(result.score, 4),
+            "params":        result.params,
+        }
+        insight = self._run_insights.get(run_id)
+        if insight:
+            d["ai_insight"] = insight
+        return d
+
     def _result_to_dict(self, r: RankedResult) -> dict:
-        return {
-            "run_id":       r.run_id,
-            "rank":         r.rank,
-            "score":        round(r.score, 4),
-            "net_profit":   round(r.net_profit, 2),
-            "calmar":       round(r.calmar, 3),
+        d = {
+            "run_id":        r.run_id,
+            "rank":          r.rank,
+            "score":         round(r.score, 4),
+            "net_profit":    round(r.net_profit, 2),
+            "calmar":        round(r.calmar, 3),
             "profit_factor": round(r.profit_factor, 3),
-            "win_rate":     round(r.win_rate, 1),
-            "max_drawdown": round(r.max_drawdown, 2),
-            "total_trades": r.total_trades,
-            "passing":      r.passing,
+            "win_rate":      round(r.win_rate, 1),
+            "max_drawdown":  round(r.max_drawdown, 2),
+            "total_trades":  r.total_trades,
+            "passing":       r.passing,
+            "params":        r.params,                     # full param dict
             "params_summary": self._params_summary(r.params),
         }
+        # Attach AI insight if available
+        insight = self._run_insights.get(r.run_id)
+        if insight:
+            d["ai_insight"] = insight
+        return d
 
     @staticmethod
     def _params_summary(params: dict) -> str:
-        """Show a few key params for display."""
-        keys = ["InpRiskPercent", "InpRRRatio", "InpMaxDailyLossPct",
-                "InpTrailStartPips", "InpMinScore", "InpSessionStart", "InpSessionEnd"]
+        """Show a few key params for display — works with any EA."""
         parts = []
-        for k in keys:
-            if k in params:
-                short = k.replace("Inp", "")
-                parts.append(f"{short}={params[k]}")
+        for k, v in list(params.items())[:8]:
+            short = k.replace("Inp", "").replace("inp", "")[:12]
+            parts.append(f"{short}={v}")
         return " | ".join(parts[:4])
 
+    def _analyze_run(self, run_id: str, metrics, trades: list, params: dict) -> list:
+        """Run Tier 1 analyzers on trade data. Always available from HTML report."""
+        findings = []
+        if not trades:
+            return findings
+
+        try:
+            trades_df = pd.DataFrame([t.model_dump() for t in trades])
+        except Exception:
+            try:
+                trades_df = pd.DataFrame([vars(t) for t in trades])
+            except Exception:
+                return findings
+
+        if trades_df.empty:
+            return findings
+
+        for analyzer_cls in (EquityCurveAnalyzer, TimePerformanceAnalyzer):
+            try:
+                az = analyzer_cls()
+                result = az.analyze(trades_df)
+                if isinstance(result, list):
+                    findings.extend(result)
+                elif result is not None:
+                    findings.append(result)
+            except Exception as e:
+                logger.debug(f"[{run_id}] {analyzer_cls.__name__} skipped: {e}")
+
+        self._run_findings[run_id] = findings
+        return findings
+
+    def _reason_about_run(
+        self, run_id: str, metrics, findings: list, params: dict
+    ) -> Optional[dict]:
+        """Call AI reasoner and emit insight via SocketIO."""
+        if not self._ai_reasoner or not self._ai_reasoner.enabled:
+            return None
+        try:
+            history = [
+                {
+                    "run_id": r.run_id, "score": r.score,
+                    "calmar": r.calmar, "pf": r.profit_factor, "phase": r.phase,
+                }
+                for r in (self.phase1_results + self.phase2_results)[-5:]
+            ]
+            insight = self._ai_reasoner.analyze(
+                findings=findings,
+                metrics=metrics,
+                run_history=history,
+                current_params=params,
+            )
+            d = insight.to_dict()
+            d["run_id"] = run_id
+            self._ai_insights.append(d)
+            self._run_insights[run_id] = d
+            self._emit("ai_insight", d)
+            return d
+        except Exception as e:
+            logger.warning(f"[{run_id}] AI reasoning failed: {e}")
+            return None
+
+    def get_latest_insight(self) -> Optional[dict]:
+        """Return the most recent AI insight."""
+        return self._ai_insights[-1] if self._ai_insights else None
+
+    def get_all_insights(self) -> list[dict]:
+        return list(self._ai_insights)
+
     def _log(self, level: str, msg: str) -> None:
         getattr(logger, level, logger.info)(msg)
         self._emit("log", {"level": level, "msg": msg})
 
+    def _emit_thinking(
+        self,
+        msg:       str,
+        kind:      str = "info",
+        iteration: Optional[int] = None,
+        meta:      Optional[dict] = None,
+    ) -> None:
+        """
+        Emit an AI-thinking stream event — distinct from system logs.
+        Shows up in the dashboard's "Live AI Thinking Feed".
+
+        kind: 'info' | 'reasoning' | 'decision' | 'warning' | 'success' | 'hypothesis'
+        """
+        payload = {
+            "msg":       msg,
+            "kind":      kind,
+            "iteration": iteration,
+            "phase":     self._phase,
+            "ts":        datetime.utcnow().isoformat(),
+        }
+        if meta:
+            payload["meta"] = meta
+        self._emit("ai_thinking", payload)
+
+    def _emit_early_termination(self, reason_code: str, message: str, details: dict = None) -> None:
+        """
+        Surface an early stop to the user.
+        reason_code examples:
+          - 'no_profit'       (Phase 1 found nothing)
+          - 'targets_met'     (AI loop hit all quality targets)
+          - 'budget_exhausted'(time budget used up)
+          - 'user_stop'       (user clicked Stop)
+          - 'stuck_escape'    (optimizer stuck, bailing)
+        """
+        payload = {
+            "reason":  reason_code,
+            "message": message,
+            "phase":   self._phase,
+            "ts":      datetime.utcnow().isoformat(),
+        }
+        if details:
+            payload["details"] = details
+        self._emit("early_termination", payload)
+
     def _emit(self, event: str, data: dict = {}) -> None:
         try:
             self.socketio.emit(event, data)
diff --git a/optimizer/session_config.py b/optimizer/session_config.py
index d67e914..22f4979 100644
--- a/optimizer/session_config.py
+++ b/optimizer/session_config.py
@@ -5,7 +5,7 @@ Passed from the /setup form → /api/start → pipeline.
 """
 from __future__ import annotations
 from dataclasses import dataclass, field, asdict
-from typing import Literal, Optional
+from typing import Literal
 
 
 ObjectiveType = Literal["balanced", "max_profit", "min_drawdown"]
@@ -42,6 +42,13 @@ class SessionConfig:
     # Phase 1 sample count (derived from budget, not user-set directly)
     phase1_samples: int = 20
 
+    # ── Autonomous AI Loop settings ───────────────────────────────────────────
+    autonomous_mode:           bool  = False  # Replace Phase 2 with AI-guided loop
+    autonomous_max_iterations: int   = 10     # Max AI-directed iterations
+    target_profit_factor:      float = 1.5    # Stop when PF ≥ this
+    target_max_drawdown_pct:   float = 20.0   # Stop when DD ≤ this %
+    target_min_calmar:         float = 0.5    # Stop when Calmar ≥ this
+
     # ── Derived helpers ───────────────────────────────────────────────────────
 
     def derive_samples(self, seconds_per_run: float = 75.0) -> None:
@@ -66,7 +73,8 @@ class SessionConfig:
 
     @property
     def total_budget_runs(self) -> int:
-        return self.phase1_samples + self.phase2_samples + self.phase3_samples
+        phase2 = self.autonomous_max_iterations if self.autonomous_mode else self.phase2_samples
+        return self.phase1_samples + phase2 + self.phase3_samples
 
     # ── Scoring weights based on objective ───────────────────────────────────
 
@@ -99,6 +107,13 @@ class SessionConfig:
         def i(key, default=0):
             try: return int(form.get(key, default))
             except (ValueError, TypeError): return default
+        def f(key, default=0.0):
+            try: return float(form.get(key, default))
+            except (ValueError, TypeError): return default
+        def b(key):
+            v = form.get(key, False)
+            if isinstance(v, bool): return v
+            return str(v).lower() in ("true", "1", "yes", "on")
 
         cfg = cls(
             ea_name         = s("ea_name", "LEGSTECH_EA_V2"),
@@ -111,6 +126,12 @@ class SessionConfig:
             objective       = s("objective", "balanced"),
             budget_minutes  = i("budget_minutes", 60),
             selected_params = form.get("selected_params", []),
+            # Autonomous loop
+            autonomous_mode           = b("autonomous_mode"),
+            autonomous_max_iterations = i("autonomous_max_iterations", 10),
+            target_profit_factor      = f("target_profit_factor", 1.5),
+            target_max_drawdown_pct   = f("target_max_drawdown_pct", 20.0),
+            target_min_calmar         = f("target_min_calmar", 0.5),
         )
         cfg.derive_samples()
         return cfg
diff --git a/optimizer_loop.py b/optimizer_loop.py
index 30bdcb0..1c9c180 100644
--- a/optimizer_loop.py
+++ b/optimizer_loop.py
@@ -30,6 +30,8 @@ from scoring.composite import CompositeScorer
 from mutation.engine import MutationEngine
 from validation.gate import ValidationGate
 from reports.writer import ReportWriter
+from analysis.ai_reasoner import AIReasoner
+from analysis.ai_reasoner_config import load_api_key
 
 import pandas as pd
 
@@ -70,6 +72,11 @@ class OptimizerLoop:
         self.run_start_ts: Optional[float] = None
         self.session_tested_deltas: list[dict] = []  # dedup within this session only
 
+        # AI Reasoning Layer
+        api_key = load_api_key(config_path)
+        self.ai_reasoner = AIReasoner(api_key=api_key)
+        self._run_history: list[dict] = []  # accumulates across iterations for AI context
+
         with open(config_path) as f:
             self.cfg = yaml.safe_load(f)
 
@@ -143,6 +150,26 @@ class OptimizerLoop:
         # Write baseline report
         findings = self._run_analysis(baseline_id, baseline_trades, baseline_metrics,
                                       analyzers, store)
+
+        # AI Reasoning — baseline
+        self._emit("log", {"level": "info", "msg": "🤖 AI Reasoner analyzing baseline..."})
+        ai_insight = self.ai_reasoner.analyze(
+            findings=findings,
+            metrics=baseline_metrics,
+            run_history=self._run_history,
+            current_params=default_params,
+        )
+        self._run_history.append({
+            "run_id": baseline_id,
+            "score":  round(baseline_metrics.composite_score, 4),
+            "calmar": round(baseline_metrics.calmar_ratio, 4),
+            "pf":     round(baseline_metrics.profit_factor, 4),
+            "phase":  "baseline",
+            "params": default_params,
+        })
+        self._emit("ai_insight", ai_insight.to_dict())
+        self._emit("log", {"level": "info", "msg": f"🤖 AI: {ai_insight.headline}"})
+
         writer.write(baseline_id, baseline_metrics, baseline_trades, findings, default_params)
 
         self.best_score    = baseline_metrics.composite_score
@@ -184,6 +211,17 @@ class OptimizerLoop:
                 self._emit("log", {"level": "warn", "msg": "No actionable findings. Stopping."})
                 break
 
+            # AI Reasoning — per iteration
+            self._emit("log", {"level": "info", "msg": f"🤖 AI Reasoner analyzing iteration {self.iteration}..."})
+            ai_insight = self.ai_reasoner.analyze(
+                findings=findings,
+                metrics=current_metrics,
+                run_history=self._run_history,
+                current_params=current_params,
+            )
+            self._emit("ai_insight", ai_insight.to_dict())
+            self._emit("log", {"level": "info", "msg": f"🤖 AI: {ai_insight.headline}"})
+
             # Mutation proposals — only dedup within this session
             hypotheses = mutator.propose(
                 findings=findings,
@@ -345,6 +383,16 @@ class OptimizerLoop:
             else:
                 no_improve_count += 1
 
+            # Track run history for AI context
+            self._run_history.append({
+                "run_id": iteration_best.run_id,
+                "score":  round(iteration_best.composite_score, 4),
+                "calmar": round(iteration_best.calmar_ratio, 4),
+                "pf":     round(iteration_best.profit_factor, 4),
+                "phase":  "explore",
+                "params": iteration_best_params,
+            })
+
             # Update score chart
             self.score_history.append({
                 "iteration": self.iteration,
diff --git a/requirements.txt b/requirements.txt
index 1c59db5..a2b11d5 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,17 +1,35 @@
-pandas>=2.1
-numpy>=1.26
-pyarrow>=14.0
-lxml>=4.9
-pydantic>=2.5
-pyyaml>=6.0
-loguru>=0.7
-rich>=13.0
-sqlalchemy>=2.0
-scipy>=1.11
-plotly>=5.18
-pytest>=7.4
-flask
-flask-socketio
-eventlet
-jinja2
-pyinstaller
+# ── Core data + numerics ─────────────────────────────────────────────────
+pandas>=2.1,<3.0
+numpy>=1.26,<2.0
+pyarrow>=14.0,<19.0
+scipy>=1.11,<2.0
+
+# ── Validation + serialization ───────────────────────────────────────────
+pydantic>=2.5,<3.0
+pyyaml>=6.0,<7.0
+lxml>=4.9,<6.0
+beautifulsoup4>=4.12,<5.0
+
+# ── Web app + realtime ───────────────────────────────────────────────────
+flask>=3.0,<4.0
+flask-socketio>=5.3,<6.0
+jinja2>=3.1,<4.0
+
+# ── Storage ──────────────────────────────────────────────────────────────
+sqlalchemy>=2.0,<3.0
+
+# ── Logging + CLI polish ─────────────────────────────────────────────────
+loguru>=0.7,<1.0
+rich>=13.0,<14.0
+
+# ── HTTP client (used by AI reasoner) ────────────────────────────────────
+requests>=2.31,<3.0
+
+# ── Process control (MT5 process supervision) ────────────────────────────
+psutil>=5.9,<6.0
+
+# ── Visualisation (optional plotting) ────────────────────────────────────
+plotly>=5.18,<6.0
+
+# ── Test ─────────────────────────────────────────────────────────────────
+pytest>=7.4,<9.0
diff --git a/screenshots/best_result_modal.png b/screenshots/best_result_modal.png
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diff --git a/screenshots/setup_autonomous_open.png b/screenshots/setup_autonomous_open.png
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literal 0
HcmV?d00001

diff --git a/ui/static/css/style.css b/ui/static/css/style.css
index 8ac67ef..767928f 100644
--- a/ui/static/css/style.css
+++ b/ui/static/css/style.css
@@ -324,3 +324,110 @@ body {
   from { opacity: 0; transform: translateY(8px); }
   to   { opacity: 1; transform: translateY(0); }
 }
+
+/* ── AI Insight Panel ─────────────────────────────────────────────────────── */
+.ai-insight-card {
+  border: 1px solid rgba(0, 212, 170, 0.25);
+  background: linear-gradient(135deg, rgba(0,212,170,0.04) 0%, rgba(124,109,250,0.04) 100%);
+  animation: slideIn 0.4s ease both;
+}
+.ai-confidence-badge {
+  font-size: 0.72rem;
+  font-weight: 600;
+  padding: 0.2rem 0.7rem;
+  border-radius: 20px;
+  text-transform: uppercase;
+  letter-spacing: 0.06em;
+}
+.ai-confidence-badge.high   { background: rgba(0,212,170,0.15); color: #00d4aa; }
+.ai-confidence-badge.medium { background: rgba(251,191,36,0.15); color: #fbbf24; }
+.ai-confidence-badge.low    { background: rgba(100,116,139,0.15); color: #94a3b8; }
+.ai-confidence-badge.analyzing { background: rgba(124,109,250,0.15); color: #7c6dfa; }
+
+.ai-headline {
+  font-size: 1.05rem;
+  font-weight: 700;
+  color: #e2e8f0;
+  margin: 0.75rem 0 0.5rem;
+  line-height: 1.4;
+}
+.ai-diagnosis {
+  font-size: 0.875rem;
+  color: #94a3b8;
+  line-height: 1.7;
+  margin-bottom: 1rem;
+}
+.ai-sections {
+  display: flex;
+  flex-direction: column;
+  gap: 0.75rem;
+}
+.ai-section {
+  background: rgba(255,255,255,0.03);
+  border: 1px solid rgba(255,255,255,0.06);
+  border-radius: 10px;
+  padding: 0.85rem 1rem;
+}
+.ai-section-label {
+  font-size: 0.72rem;
+  font-weight: 700;
+  text-transform: uppercase;
+  letter-spacing: 0.08em;
+  color: #64748b;
+  margin-bottom: 0.6rem;
+}
+.ai-list {
+  list-style: none;
+  padding: 0;
+  margin: 0;
+  display: flex;
+  flex-direction: column;
+  gap: 0.35rem;
+}
+.ai-list li {
+  font-size: 0.83rem;
+  color: #cbd5e1;
+  padding-left: 1.1rem;
+  position: relative;
+  line-height: 1.5;
+}
+.ai-list li::before {
+  content: "→";
+  position: absolute;
+  left: 0;
+  color: #00d4aa;
+  font-size: 0.75rem;
+}
+.ai-list-warn li::before { color: #fbbf24; content: "⚠"; }
+
+.ai-suggestions {
+  display: flex;
+  flex-direction: column;
+  gap: 0.5rem;
+}
+.ai-suggestion-row {
+  display: grid;
+  grid-template-columns: 180px 80px 80px 1fr;
+  align-items: center;
+  gap: 0.75rem;
+  font-size: 0.82rem;
+  padding: 0.4rem 0.5rem;
+  border-radius: 6px;
+  background: rgba(255,255,255,0.02);
+}
+.ai-param-name {
+  font-family: 'JetBrains Mono', monospace;
+  font-size: 0.78rem;
+  color: #7c6dfa;
+}
+.ai-param-from { color: #64748b; text-align: center; }
+.ai-param-to {
+  color: #00d4aa;
+  font-weight: 600;
+  text-align: center;
+}
+.ai-param-reason {
+  color: #94a3b8;
+  font-size: 0.78rem;
+  line-height: 1.4;
+}
diff --git a/ui/static/js/dashboard.js b/ui/static/js/dashboard.js
index 7b0666d..f433b78 100644
--- a/ui/static/js/dashboard.js
+++ b/ui/static/js/dashboard.js
@@ -1,466 +1,1753 @@
 /**
- * dashboard.js — Smart Optimizer Live Dashboard
- * Handles all SocketIO events from the 3-phase pipeline.
+ * dashboard.js — APEX AI-Powered EA Optimizer
+ * Handles all SocketIO events, chart rendering, and UI state.
  */
 
-// ── Chart Setup ───────────────────────────────────────────────────────────────
-const ctx   = document.getElementById('scoreChart').getContext('2d');
-const chart = new Chart(ctx, {
+'use strict';
+
+/* ══════════════════════════════════════════════════════════════════════
+   UTILITIES
+══════════════════════════════════════════════════════════════════════ */
+
+function el(id) { return document.getElementById(id); }
+
+function fmtMoney(v) {
+  const n = parseFloat(v) || 0;
+  const abs = Math.abs(n);
+  let s;
+  if (abs >= 1000000) s = (n / 1000000).toFixed(2) + 'M';
+  else if (abs >= 1000) s = (n / 1000).toFixed(1) + 'k';
+  else s = n.toFixed(2);
+  return (n >= 0 ? '$' : '-$') + (n < 0 ? s.replace('-', '') : s);
+}
+
+function fmtPct(v, decimals) {
+  return (parseFloat(v) || 0).toFixed(decimals != null ? decimals : 2) + '%';
+}
+
+function fmtTime(secs) {
+  const s = Math.floor(secs);
+  const h = Math.floor(s / 3600);
+  const m = Math.floor((s % 3600) / 60);
+  const sec = s % 60;
+  if (h > 0) return h + 'h ' + String(m).padStart(2, '0') + 'm';
+  return String(m).padStart(2, '0') + ':' + String(sec).padStart(2, '0');
+}
+
+function nowStr() {
+  return new Date().toLocaleTimeString('en-US', { hour12: false });
+}
+
+function escapeHtml(str) {
+  return String(str)
+    .replace(/&/g, '&amp;')
+    .replace(/</g, '&lt;')
+    .replace(/>/g, '&gt;')
+    .replace(/"/g, '&quot;');
+}
+
+function safe(id, fn) {
+  const e = el(id);
+  if (e) fn(e);
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   GLOBAL STATE
+══════════════════════════════════════════════════════════════════════ */
+
+const state = {
+  runs: 0,
+  isRunning: false,
+  startTime: null,
+  elapsedTimer: null,
+  logCount: 0,
+  bestProfit: null,
+  sparkData: { profit: [], dd: [], pf: [], trades: [], runs: [] },
+};
+
+/* ══════════════════════════════════════════════════════════════════════
+   CHART.JS DEFAULTS
+══════════════════════════════════════════════════════════════════════ */
+
+Chart.defaults.color = '#64748b';
+Chart.defaults.font.family = "'Inter', -apple-system, sans-serif";
+Chart.defaults.font.size = 11;
+
+/* ── Equity Curve ─────────────────────────────────────────────────── */
+
+const equityChart = new Chart(el('equityChart').getContext('2d'), {
   type: 'line',
   data: {
     labels: [],
     datasets: [
       {
-        label: 'Session Score',
+        label: 'Equity',
         data: [],
-        borderColor: '#00d4aa',
-        backgroundColor: 'rgba(0,212,170,0.08)',
-        borderWidth: 2,
-        pointRadius: 4,
-        pointHoverRadius: 6,
-        pointBackgroundColor: ctx => {
-          const v = ctx.raw;
-          return (v !== null && v > 0) ? '#00d4aa' : '#ef4444';
+        borderColor: '#4f46e5',
+        backgroundColor: (ctx) => {
+          const { ctx: c, chartArea } = ctx.chart;
+          if (!chartArea) return 'transparent';
+          const g = c.createLinearGradient(0, chartArea.top, 0, chartArea.bottom);
+          g.addColorStop(0, 'rgba(79,70,229,0.22)');
+          g.addColorStop(1, 'rgba(79,70,229,0)');
+          return g;
         },
-        tension: 0.35,
-        fill: true,
+        borderWidth: 2, pointRadius: 0, pointHoverRadius: 4,
+        pointHoverBackgroundColor: '#4f46e5', tension: 0.4, fill: true,
       },
       {
-        label: 'Calmar Ratio',
+        label: 'Balance',
         data: [],
-        borderColor: '#7c6dfa',
+        borderColor: '#00d4aa',
+        backgroundColor: 'transparent',
         borderWidth: 1.5,
-        pointRadius: 2,
-        borderDash: [4, 3],
-        tension: 0.35,
-        fill: false,
-      }
-    ]
+        borderDash: [5, 4],
+        pointRadius: 0, pointHoverRadius: 4,
+        pointHoverBackgroundColor: '#00d4aa', tension: 0.4, fill: false,
+      },
+    ],
   },
   options: {
-    responsive: true,
-    maintainAspectRatio: false,
+    responsive: true, maintainAspectRatio: false,
     animation: { duration: 400 },
+    interaction: { intersect: false, mode: 'index' },
     plugins: {
-      legend: {
-        labels: { color: '#94a3b8', font: { family: 'Inter', size: 11 }, boxWidth: 12 }
-      },
+      legend: { display: false },
       tooltip: {
-        backgroundColor: '#141b27',
-        borderColor: 'rgba(255,255,255,0.1)',
-        borderWidth: 1,
-        titleColor: '#e2e8f0',
-        bodyColor: '#94a3b8',
-        callbacks: {
-          label: ctx => {
-            if (ctx.dataset.label === 'Session Score') return ` Score: ${(ctx.raw || 0).toFixed(4)}`;
-            return ` Calmar: ${(ctx.raw || 0).toFixed(3)}`;
-          }
-        }
-      }
+        backgroundColor: '#0f1629', borderColor: 'rgba(255,255,255,0.1)', borderWidth: 1,
+        padding: 10, titleColor: '#94a3b8', bodyColor: '#e2e8f0',
+        callbacks: { label: (ctx) => ' ' + ctx.dataset.label + ': $' + ctx.parsed.y.toFixed(2) },
+      },
     },
     scales: {
-      x: { ticks: { color: '#475569', font: { size: 10 }, maxTicksLimit: 12 }, grid: { color: 'rgba(255,255,255,0.04)' } },
-      y: { min: 0, max: 1, ticks: { color: '#475569', font: { size: 10 } }, grid: { color: 'rgba(255,255,255,0.04)' } }
-    }
-  }
+      x: { grid: { color: 'rgba(255,255,255,0.04)' }, ticks: { maxTicksLimit: 8, maxRotation: 0, color: '#475569', font: { size: 10 } }, border: { display: false } },
+      y: { grid: { color: 'rgba(255,255,255,0.04)' }, ticks: { maxTicksLimit: 6, color: '#475569', font: { size: 10 }, callback: (v) => '$' + v.toFixed(0) }, border: { display: false } },
+    },
+  },
 });
 
-// ── State ─────────────────────────────────────────────────────────────────────
-let startTs    = null;
-let elapsedTimer = null;
-let findingsCount = 0;
-let runCount      = 0;
-let bestScore     = 0;
-let candCount     = 0;
-let totalRuns     = 0;
+/* ── Drawdown Chart ───────────────────────────────────────────────── */
 
-// ── SocketIO ──────────────────────────────────────────────────────────────────
-const socket = io();
-
-socket.on('connect', () => addLog('info', '🔗 Connected to optimizer server'));
-socket.on('disconnect', () => addLog('warning', '⚡ Disconnected from server'));
-
-// Status sync on connect
-socket.on('status_sync', (s) => {
-  setStatus(s.state, s.phase);
-  if (s.ea_name && s.symbol && s.timeframe) {
-    document.getElementById('session-label').textContent =
-      `${s.ea_name} · ${s.symbol} · ${s.timeframe}`;
-  }
-  totalRuns = s.total_runs || 0;
-  updateRunCount(s.run_count || 0);
-  if (s.state === 'running') {
-    document.getElementById('progress-wrap').style.display = '';
-    document.getElementById('btn-stop').classList.remove('hidden');
-  }
+const drawdownChart = new Chart(el('drawdownChart').getContext('2d'), {
+  type: 'line',
+  data: {
+    labels: [],
+    datasets: [{
+      label: 'Drawdown',
+      data: [],
+      borderColor: '#ef4444',
+      backgroundColor: (ctx) => {
+        const { ctx: c, chartArea } = ctx.chart;
+        if (!chartArea) return 'transparent';
+        const g = c.createLinearGradient(0, chartArea.top, 0, chartArea.bottom);
+        g.addColorStop(0, 'rgba(239,68,68,0.35)');
+        g.addColorStop(1, 'rgba(239,68,68,0.02)');
+        return g;
+      },
+      borderWidth: 1.5, pointRadius: 0, pointHoverRadius: 3, tension: 0.4, fill: true,
+    }],
+  },
+  options: {
+    responsive: true, maintainAspectRatio: false,
+    animation: { duration: 400 },
+    interaction: { intersect: false, mode: 'index' },
+    plugins: {
+      legend: { display: false },
+      tooltip: {
+        backgroundColor: '#0f1629', borderColor: 'rgba(255,255,255,0.1)', borderWidth: 1,
+        padding: 8, titleColor: '#94a3b8', bodyColor: '#ef4444',
+        callbacks: { label: (ctx) => ' Drawdown: ' + ctx.parsed.y.toFixed(2) + '%' },
+      },
+    },
+    scales: {
+      x: { grid: { color: 'rgba(255,255,255,0.04)' }, ticks: { maxTicksLimit: 8, maxRotation: 0, color: '#475569', font: { size: 10 } }, border: { display: false } },
+      y: { grid: { color: 'rgba(255,255,255,0.04)' }, ticks: { maxTicksLimit: 4, color: '#475569', font: { size: 10 }, callback: (v) => v.toFixed(1) + '%' }, border: { display: false } },
+    },
+  },
 });
 
-socket.on('status_change', (d) => {
-  setStatus(d.state, d.phase);
-  if (d.state === 'running') {
-    startTs = Date.now();
-    startElapsedTimer();
-    document.getElementById('progress-wrap').style.display = '';
-    document.getElementById('btn-stop').classList.remove('hidden');
-  }
-  if (d.state === 'idle' || d.state === 'stopping') {
-    document.getElementById('btn-stop').classList.add('hidden');
-  }
-});
+/* ── Sparklines ───────────────────────────────────────────────────── */
 
-// Each run completes
-socket.on('run_complete', (d) => {
-  updateRunCount((d.run_number != null) ? null : runCount + 1, d);
+const sparklineCharts = {};
 
-  // Update metrics
-  const profit = d.net_profit || 0;
-  el('m-profit').textContent  = `$${profit.toFixed(0)}`;
-  el('m-profit').className    = 'metric-val ' + (profit >= 0 ? 'profit-pos' : 'profit-neg');
-  el('m-calmar').textContent  = (d.calmar || 0).toFixed(3);
-  el('m-pf').textContent      = d.profit_factor != null ? (d.profit_factor).toFixed(2) : '—';
-  el('m-dd').textContent      = d.max_drawdown != null ? `${d.max_drawdown.toFixed(1)}%` : '—';
-  el('m-wr').textContent      = d.win_rate != null ? `${d.win_rate.toFixed(1)}%` : '—';
-  el('m-trades').textContent  = d.total_trades != null ? d.total_trades : '—';
-  el('current-run-id').textContent = d.run_id || '—';
-
-  // Session score (0–1)
-  const score    = d.score || 0;
-  const scoreStr = score.toFixed(4);
-  el('m-score').textContent = d.passing ? scoreStr : 'failing';
-  el('score-bar-fill').style.width = `${Math.round(score * 100)}%`;
-
-  // Update best score header
-  if (d.passing && score > bestScore) {
-    bestScore = score;
-    el('hdr-score').textContent = scoreStr;
-  }
-
-  // Add to chart
-  const label = d.run_id ? d.run_id.slice(-6) : `${runCount}`;
-  chart.data.labels.push(label);
-  chart.data.datasets[0].data.push(d.passing ? score : 0);
-
-  // Calmar normalized to 0-1 range (cap at 3)
-  const calmarNorm = Math.min(Math.max((d.calmar || 0) / 3.0, 0), 1);
-  chart.data.datasets[1].data.push(d.passing ? calmarNorm : 0);
-
-  chart.update('none');
-  el('chart-badge').textContent = `${chart.data.labels.length} runs`;
-
-  // Progress bar
-  if (d.progress_pct != null) {
-    el('progress-bar-fill').style.width = `${d.progress_pct}%`;
-  }
-  if (d.phase) updatePhaseLabel(d.phase, d.run_number, d.total);
-  if (d.budget_summary) el('progress-budget').textContent = d.budget_summary;
-
-  // Add to best configs panel if profitable
-  if (d.passing) {
-    addCandidate(d);
-  }
-});
-
-// Phase start
-socket.on('phase_start', (d) => {
-  const labels = { phase1: 'Phase 1: Broad Discovery', phase2: 'Phase 2: Refinement', phase3: 'Phase 3: Validation' };
-  el('progress-phase').textContent = labels[d.phase] || d.phase;
-  el('progress-count').textContent = `0 / ${d.total || '?'}`;
-  setPhaseActive(d.phase);
-  if (d.phase === 'phase2') {
-    markPhaseDone('phase1');
-    el('phase1-results-card').style.display = '';
-  }
-  if (d.phase === 'phase3') {
-    markPhaseDone('phase2');
-  }
-});
-
-// Phase 1 complete — show results table
-socket.on('phase1_complete', (d) => {
-  el('phase1-results-card').style.display = '';
-  el('phase1-badge').textContent = `${d.n_passing}/${d.total_tested} profitable`;
-  renderPhase1Table(d.top_results || []);
-  addLog('info', `━━ Phase 1 done: ${d.n_passing}/${d.total_tested} profitable configs found. Starting refinement...`);
-});
-
-// Phase 2 complete
-socket.on('phase2_complete', (d) => {
-  addLog('success', `✅ Phase 2 done. Best: ${d.best_run_id} · Profit: $${d.best_profit} · Calmar: ${d.best_calmar}`);
-});
-
-// No profitable configuration found
-socket.on('no_profitable_config', (d) => {
-  el('no-profit-banner').style.display = '';
-  el('no-profit-msg').textContent = d.msg || 'No profitable configuration found.';
-  el('progress-wrap').style.display = 'none';
-  addLog('error', '❌ ' + (d.msg || 'No profitable config found'));
-});
-
-// Optimization complete — show verdict
-socket.on('optimization_complete', (d) => {
-  markPhaseDone('phase3');
-  markPhaseDone('done');
-  setStatus('idle', 'done');
-  stopElapsedTimer();
-
-  el('progress-wrap').style.display = 'none';
-  el('btn-stop').classList.add('hidden');
-
-  renderVerdict(d);
-  addLog(d.verdict === 'RECOMMENDED' ? 'success' : 'warning',
-    `🏁 Optimization complete! ${d.verdict} · `+
-    `Profit: $${d.net_profit} · Calmar: ${d.calmar} · Runs: ${d.total_runs} · ${d.elapsed_min}min`
-  );
-});
-
-// Log
-socket.on('log', (d) => addLog(d.level, d.msg));
-
-// Error
-socket.on('error', (d) => addLog('error', '❌ ' + (d.msg || 'Unknown error')));
-
-
-// ── Actions ───────────────────────────────────────────────────────────────────
-
-function stopOptimizer() {
-  fetch('/api/stop', { method: 'POST' }).catch(() => {});
-  addLog('warning', '⏹ Stop requested...');
-}
-
-function clearLog() {
-  el('log-feed').innerHTML = '';
-}
-
-
-// ── Rendering helpers ─────────────────────────────────────────────────────────
-
-function renderPhase1Table(results) {
-  const tbody = el('phase1-tbody');
-  tbody.innerHTML = '';
-  results.forEach((r, i) => {
-    const tr = document.createElement('tr');
-    if (i === 0) tr.className = 'rank-1';
-    const profitClass = r.net_profit >= 0 ? 'profit-pos' : 'profit-neg';
-    const badge = r.passing
-      ? `<span class="badge-pass">✓ pass</span>`
-      : `<span class="badge-fail">fail</span>`;
-    tr.innerHTML = `
-      <td>#${r.rank || i+1} ${i === 0 ? '🥇' : ''}</td>
-      <td class="${profitClass}">$${(r.net_profit||0).toFixed(0)}</td>
-      <td>${(r.calmar||0).toFixed(3)}</td>
-      <td>${(r.profit_factor||0).toFixed(2)}</td>
-      <td>${(r.win_rate||0).toFixed(1)}%</td>
-      <td>${(r.max_drawdown||0).toFixed(1)}%</td>
-      <td>${r.total_trades||0}</td>
-      <td>${(r.score||0).toFixed(4)}</td>
-    `;
-    tbody.appendChild(tr);
+function createSparkline(canvasId, color, fillColor) {
+  const canvas = el(canvasId);
+  if (!canvas) return null;
+  return new Chart(canvas.getContext('2d'), {
+    type: 'line',
+    data: { labels: [], datasets: [{ data: [], borderColor: color, backgroundColor: fillColor || 'transparent', borderWidth: 1.5, pointRadius: 0, tension: 0.4, fill: !!fillColor }] },
+    options: { responsive: false, animation: { duration: 250 }, plugins: { legend: { display: false }, tooltip: { enabled: false } }, scales: { x: { display: false }, y: { display: false } } },
   });
 }
 
-function renderVerdict(d) {
-  const banner = el('verdict-banner');
-  const icons  = { RECOMMENDED: '✅', RISKY: '⚠️', NOT_RELIABLE: '❌' };
-  const labels = {
+function initSparklines() {
+  sparklineCharts.profit = createSparkline('spark-profit', '#10b981', 'rgba(16,185,129,0.12)');
+  sparklineCharts.dd     = createSparkline('spark-dd',     '#ef4444', 'rgba(239,68,68,0.12)');
+  sparklineCharts.pf     = createSparkline('spark-pf',     '#f59e0b', 'rgba(245,158,11,0.10)');
+  sparklineCharts.trades = createSparkline('spark-trades',  '#00d4aa', 'rgba(0,212,170,0.10)');
+  sparklineCharts.runs   = createSparkline('spark-runs',   '#7c6dfa', 'rgba(124,109,250,0.10)');
+}
+
+function pushSparkData(key, value) {
+  const arr = state.sparkData[key];
+  arr.push(value);
+  if (arr.length > 20) arr.shift();
+  const c = sparklineCharts[key];
+  if (!c) return;
+  c.data.labels = arr.map((_, i) => i);
+  c.data.datasets[0].data = arr;
+  c.update('none');
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   METRIC CARDS
+══════════════════════════════════════════════════════════════════════ */
+
+function updateMetricCards(d) {
+  const profit = parseFloat(d.net_profit  || d.best_net_profit  || 0);
+  const maxDD  = parseFloat(d.max_drawdown || d.best_max_drawdown || d.max_dd || 0);
+  const pf     = parseFloat(d.profit_factor || d.best_pf || d.pf || 0);
+  const trades = parseInt(d.total_trades  || d.best_total_trades || d.trades || 0, 10);
+
+  // Net Profit
+  safe('m-net-profit', e => { e.textContent = fmtMoney(profit); });
+  if (state.bestProfit === null) state.bestProfit = profit;
+  const delta = state.bestProfit !== 0 ? ((profit - state.bestProfit) / Math.abs(state.bestProfit) * 100) : 0;
+  safe('m-net-profit-delta-val', e => { e.textContent = (delta >= 0 ? '+' : '') + delta.toFixed(1) + '%'; });
+  const arrow = el('m-net-profit-delta') && el('m-net-profit-delta').querySelector('span:first-child');
+  if (arrow) { arrow.textContent = delta >= 0 ? '↑' : '↓'; arrow.className = delta >= 0 ? 'delta-up' : 'delta-down'; }
+  pushSparkData('profit', profit);
+
+  // Max Drawdown
+  safe('m-max-dd', e => { e.textContent = fmtPct(maxDD); });
+  safe('max-dd-badge', e => { e.textContent = 'Max DD: ' + fmtPct(maxDD, 1); });
+  pushSparkData('dd', maxDD);
+
+  // Profit Factor
+  safe('m-pf', e => { e.textContent = pf.toFixed(2); });
+  safe('m-pf-quality', e => {
+    if (pf >= 2)       { e.textContent = 'Excellent'; e.style.color = 'var(--green)'; }
+    else if (pf >= 1.5){ e.textContent = 'Good';      e.style.color = 'var(--teal)'; }
+    else if (pf >= 1)  { e.textContent = 'Marginal';  e.style.color = 'var(--yellow)'; }
+    else               { e.textContent = 'Poor';       e.style.color = 'var(--red)'; }
+  });
+  pushSparkData('pf', pf);
+
+  // Trades
+  safe('m-trades', e => { e.textContent = trades.toLocaleString(); });
+  pushSparkData('trades', trades);
+}
+
+function updateRunsCounter() {
+  state.runs++;
+  safe('m-runs', e => { e.textContent = state.runs.toString(); });
+  pushSparkData('runs', state.runs);
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   AI GAUGE
+══════════════════════════════════════════════════════════════════════ */
+
+const CIRCUMFERENCE = 163.4; // 2π × 26
+
+function updateAIGauge(pct, label) {
+  const color = { high: '#10b981', medium: '#f59e0b', low: '#ef4444' }[label] || '#00d4aa';
+  safe('ai-gauge-arc', e => {
+    e.style.strokeDashoffset = (CIRCUMFERENCE * (1 - pct / 100)).toString();
+    e.style.stroke = color;
+  });
+  safe('ai-gauge-pct', e => { e.textContent = pct + '%'; });
+  safe('ai-conf-label', e => {
+    e.textContent = label ? label.charAt(0).toUpperCase() + label.slice(1) : '—';
+    e.style.color = color;
+  });
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   HEADER SCORE
+══════════════════════════════════════════════════════════════════════ */
+
+function updateHeaderScore(score, delta) {
+  const s = parseFloat(score);
+  if (isNaN(s)) return;
+  safe('hdr-score', e => { e.textContent = s.toFixed(3); });
+  if (delta != null) {
+    const d2 = parseFloat(delta);
+    if (!isNaN(d2)) {
+      const sign = d2 >= 0 ? '+' : '';
+      safe('hdr-score-delta', e => {
+        e.textContent = sign + d2.toFixed(3) + ' improvement';
+        e.style.color = d2 >= 0 ? 'var(--green)' : 'var(--red)';
+      });
+    }
+  } else {
+    safe('hdr-score-delta', e => { e.textContent = 'Latest result'; e.style.color = ''; });
+  }
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   AI PANEL — shared update function
+══════════════════════════════════════════════════════════════════════ */
+
+function updateAIPanel(d) {
+  if (!d) return;
+
+  safe('ai-waiting', e => { e.style.display = 'none'; });
+  safe('ai-content', e => { e.style.display = ''; });
+
+  // Preview (always visible) — headline + diagnosis
+  if (d.headline) {
+    safe('ai-headline', e => { e.textContent = d.headline; e.style.display = ''; });
+  }
+  if (d.diagnosis) {
+    safe('ai-diagnosis-text', e => { e.textContent = d.diagnosis; });
+  }
+
+  // Details section — populate but keep collapsed until user clicks "View Details"
+  const patterns = d.patterns || d.strengths || [];
+  if (patterns.length) {
+    safe('ai-strengths-section', e => { e.style.display = ''; });
+    safe('ai-strengths-list', e => {
+      e.innerHTML = patterns.slice(0, 4).map(p => '<li>' + escapeHtml(p) + '</li>').join('');
+    });
+  }
+
+  const suggestions = d.suggestions || [];
+  if (suggestions.length) {
+    const s = suggestions[0];
+    let txt = '';
+    if (typeof s === 'string') {
+      txt = s;
+    } else {
+      txt = s.reason || '';
+      if (s.param || s.parameter) {
+        const param = s.param || s.parameter;
+        txt += ' (' + param + ': ' + (s.from !== undefined ? s.from : '') + ' → ' + (s.to !== undefined ? s.to : '') + ')';
+      }
+    }
+    safe('ai-suggestion-text', e => { e.textContent = txt; });
+    safe('ai-suggestion-box', e => { e.style.display = ''; });
+  }
+
+  const risks = d.risk_flags || d.risks || [];
+  if (risks.length) {
+    safe('ai-risks-section', e => { e.style.display = ''; });
+    safe('ai-risks-list', e => {
+      e.innerHTML = risks.slice(0, 3).map(r => '<li>' + escapeHtml(r) + '</li>').join('');
+    });
+  }
+
+  // Confidence (always shown at bottom)
+  const conf = (typeof d.confidence === 'string' ? d.confidence : 'medium').toLowerCase();
+  safe('ai-panel-conf-badge', e => {
+    e.textContent = conf;
+    e.className = 'ai-conf-badge ' + conf;
+  });
+
+  const pctMap = { high: 87, medium: 62, low: 38 };
+  const pct = typeof d.confidence_pct === 'number' ? d.confidence_pct : (pctMap[conf] || 62);
+  updateAIGauge(pct, conf);
+
+  if (d.run_id) safe('ai-run-ref', e => { e.textContent = 'Run: ' + d.run_id; });
+
+  safe('ai-badge', e => { e.style.display = ''; });
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   RECENT RUNS TABLE
+══════════════════════════════════════════════════════════════════════ */
+
+const MAX_RECENT_RUNS = 8;
+const recentRuns = [];
+
+function addRecentRun(d) {
+  const profit = parseFloat(d.net_profit || 0);
+  const pf     = parseFloat(d.profit_factor || d.pf || 0);
+  const maxDD  = parseFloat(d.max_drawdown || d.max_dd || 0);
+  const run_id = d.run_id || null;
+
+  // Derive verdict: use explicit field if present, otherwise infer from passing
+  let verdict = (d.verdict || '').toUpperCase().replace(/ /g, '_');
+  if (!verdict) {
+    verdict = d.passing === false ? 'NOT_RELIABLE' : (d.passing === true ? 'PASSING' : 'PENDING');
+  }
+
+  const verdictClass = {
+    RECOMMENDED:  'verdict-recommended',
+    PASSING:      'verdict-recommended',
+    RISKY:        'verdict-risky',
+    PENDING:      'verdict-risky',
+    NOT_RELIABLE: 'verdict-not-reliable',
+  }[verdict] || 'verdict-risky';
+
+  const verdictLabel = {
     RECOMMENDED:  'Recommended',
+    PASSING:      'Passing',
     RISKY:        'Risky',
+    PENDING:      'Pending',
     NOT_RELIABLE: 'Not Reliable',
-  };
-  const subs = {
-    RECOMMENDED:  'Consistent returns with controlled drawdown. Ready to deploy.',
-    RISKY:        'Profitable in-sample but shows signs of fragility or OOS degradation. Use with caution.',
-    NOT_RELIABLE: 'Results are inconsistent or not profitable enough. Consider different settings.',
-  };
+  }[verdict] || verdict.replace(/_/g, ' ');
 
-  const profitClass = d.net_profit >= 0 ? 'profit-pos' : 'profit-neg';
-  const oos = d.oos_profit != null
-    ? `<div class="verdict-metric"><div class="verdict-metric-val ${d.oos_profit>=0?'profit-pos':'profit-neg'}" >$${d.oos_profit.toFixed(0)}</div><div class="verdict-metric-lbl">OOS Profit</div></div>`
-    : '';
+  recentRuns.unshift({ profit, pf, maxDD, verdictClass, verdictLabel, run_id });
+  if (recentRuns.length > MAX_RECENT_RUNS) recentRuns.pop();
 
-  banner.className = `verdict-banner ${d.verdict}`;
-  banner.innerHTML = `
-    <div class="verdict-header verdict-${d.verdict}">
-      <div class="verdict-icon">${icons[d.verdict] || '?'}</div>
-      <div>
-        <div class="verdict-title">${labels[d.verdict] || d.verdict}</div>
-        <div class="verdict-sub">${subs[d.verdict] || ''}</div>
-      </div>
-    </div>
-    <div class="verdict-metrics">
-      <div class="verdict-metric">
-        <div class="verdict-metric-val ${profitClass}">$${(d.net_profit||0).toFixed(0)}</div>
-        <div class="verdict-metric-lbl">Net Profit</div>
-      </div>
-      <div class="verdict-metric">
-        <div class="verdict-metric-val">${(d.calmar||0).toFixed(2)}</div>
-        <div class="verdict-metric-lbl">Calmar</div>
-      </div>
-      <div class="verdict-metric">
-        <div class="verdict-metric-val">${(d.win_rate||0).toFixed(1)}%</div>
-        <div class="verdict-metric-lbl">Win Rate</div>
-      </div>
-      <div class="verdict-metric">
-        <div class="verdict-metric-val">${(d.max_drawdown||0).toFixed(1)}%</div>
-        <div class="verdict-metric-lbl">Max DD</div>
-      </div>
-      ${oos}
-    </div>
-    <div class="verdict-actions">
-      ${d.set_file_url ? `<a href="${d.set_file_url}" class="btn-download" download>⬇ Download .set File</a>` : ''}
-      <a href="/reports" class="btn-new-run">📁 View Full Report</a>
-      <a href="/setup" class="btn-new-run">⚡ New Optimization</a>
-    </div>
-  `;
-  banner.style.display = '';
+  const tbody = el('recent-runs-tbody');
+  if (!tbody) return;
+  tbody.innerHTML = recentRuns.map((r, i) => `
+    <tr>
+      <td class="run-num">#${state.runs - i}</td>
+      <td class="${r.profit >= 0 ? 'profit-pos' : 'profit-neg'}">${fmtMoney(r.profit)}</td>
+      <td style="color:var(--yellow);font-weight:600;">${r.pf.toFixed(2)}</td>
+      <td style="color:var(--red);">${r.maxDD.toFixed(1)}%</td>
+      <td><span class="${r.verdictClass}">${r.verdictLabel}</span></td>
+      <td>${r.run_id ? `<button class="detail-btn" onclick="openRunDetail('${escapeHtml(r.run_id)}')">Details</button>` : ''}</td>
+    </tr>
+  `).join('');
 }
 
-function addCandidate(d) {
-  const list = el('candidates-list');
-  const empty = list.querySelector('.cand-empty');
-  if (empty) empty.remove();
+/* ══════════════════════════════════════════════════════════════════════
+   PARAMETERS TABLE
+══════════════════════════════════════════════════════════════════════ */
 
-  candCount++;
-  el('cand-count').textContent = `${candCount} config${candCount !== 1 ? 's' : ''}`;
+function updateParamsTable(params) {
+  if (!params || typeof params !== 'object') return;
+  const tbody = el('params-tbody');
+  if (!tbody) return;
+  const entries = Object.entries(params);
+  if (!entries.length) return;
 
-  // Keep only top 10
-  if (list.children.length >= 10) {
-    list.removeChild(list.lastChild);
+  tbody.innerHTML = entries.slice(0, 8).map(([key, val], i) => {
+    const impactClass = i < 2 ? 'impact-high' : i < 5 ? 'impact-medium' : 'impact-low';
+    const impactLabel = i < 2 ? 'High' : i < 5 ? 'Medium' : 'Low';
+    const display = typeof val === 'number' ? val.toFixed(val % 1 !== 0 ? 4 : 0) : val;
+    return `
+      <tr>
+        <td class="param-name">${escapeHtml(key)}</td>
+        <td class="param-val">${escapeHtml(String(display))}</td>
+        <td><span class="${impactClass}">${impactLabel}</span></td>
+      </tr>
+    `;
+  }).join('');
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   CHART UPDATES
+══════════════════════════════════════════════════════════════════════ */
+
+function pushEquityPoint(equity, balance, label) {
+  const MAX = 80;
+  const lbl = label || nowStr();
+  equityChart.data.labels.push(lbl);
+  equityChart.data.datasets[0].data.push(parseFloat(equity) || 0);
+  equityChart.data.datasets[1].data.push(parseFloat(balance) || 0);
+  if (equityChart.data.labels.length > MAX) {
+    equityChart.data.labels.shift();
+    equityChart.data.datasets.forEach(ds => ds.data.shift());
+  }
+  equityChart.update('none');
+}
+
+function pushDDPoint(dd, label) {
+  const MAX = 80;
+  const lbl = label || nowStr();
+  drawdownChart.data.labels.push(lbl);
+  drawdownChart.data.datasets[0].data.push(parseFloat(dd) || 0);
+  if (drawdownChart.data.labels.length > MAX) {
+    drawdownChart.data.labels.shift();
+    drawdownChart.data.datasets[0].data.shift();
+  }
+  drawdownChart.update('none');
+}
+
+function populateChartsFromEquityCurve(curve) {
+  if (!Array.isArray(curve) || !curve.length) return;
+  equityChart.data.labels = [];
+  equityChart.data.datasets[0].data = [];
+  equityChart.data.datasets[1].data = [];
+  drawdownChart.data.labels = [];
+  drawdownChart.data.datasets[0].data = [];
+
+  const step = Math.max(1, Math.floor(curve.length / 80));
+  curve.forEach((pt, i) => {
+    if (i % step !== 0 && i !== curve.length - 1) return;
+    const lbl = pt.date || pt.time || String(i + 1);
+    equityChart.data.labels.push(lbl);
+    equityChart.data.datasets[0].data.push(parseFloat(pt.equity || pt.Equity || 0));
+    equityChart.data.datasets[1].data.push(parseFloat(pt.balance || pt.Balance || 0));
+    drawdownChart.data.labels.push(lbl);
+    drawdownChart.data.datasets[0].data.push(parseFloat(pt.drawdown || pt.Drawdown || 0));
+  });
+
+  equityChart.update();
+  drawdownChart.update();
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   PROGRESS
+══════════════════════════════════════════════════════════════════════ */
+
+function updateProgress(d) {
+  // Use progress_pct if available, fall back to run_number/total
+  let pct = null;
+  if (d.progress_pct !== undefined) pct = d.progress_pct;
+  else if (d.run_number !== undefined && d.total) pct = Math.round(d.run_number / d.total * 100);
+
+  if (pct !== null) {
+    const p = Math.min(100, pct);
+    safe('opt-progress-fill', e => { e.style.width = p + '%'; });
+    safe('hdr-prog-fill',     e => { e.style.width = p + '%'; });
+    safe('hdr-pct',           e => { e.textContent = p + '% Complete'; });
   }
 
-  const card = document.createElement('div');
-  card.className = 'cand-card';
-  const profitClass = (d.net_profit||0) >= 0 ? 'profit-pos' : 'profit-neg';
-  card.innerHTML = `
-    <div class="cand-header">
-      <span class="cand-rank">${d.phase?.toUpperCase() || 'RUN'} · Score ${(d.score||0).toFixed(4)}</span>
-      <span class="cand-run-id">${d.run_id}</span>
-    </div>
-    <div class="cand-score-row">
-      <div class="cand-metric">
-        <div class="cand-metric-lbl">Profit</div>
-        <div class="cand-metric-val ${profitClass}">$${(d.net_profit||0).toFixed(0)}</div>
-      </div>
-      <div class="cand-metric">
-        <div class="cand-metric-lbl">Calmar</div>
-        <div class="cand-metric-val">${(d.calmar||0).toFixed(3)}</div>
-      </div>
-      <div class="cand-metric">
-        <div class="cand-metric-lbl">Win%</div>
-        <div class="cand-metric-val">${(d.win_rate||0).toFixed(1)}%</div>
-      </div>
-      <div class="cand-metric">
-        <div class="cand-metric-lbl">DD%</div>
-        <div class="cand-metric-val">${(d.max_drawdown||0).toFixed(1)}%</div>
-      </div>
-      <div class="cand-metric">
-        <div class="cand-metric-lbl">Trades</div>
-        <div class="cand-metric-val">${d.total_trades||0}</div>
-      </div>
-    </div>
-  `;
-  list.insertBefore(card, list.firstChild);
-}
-
-function addLog(level, msg) {
-  const feed = el('log-feed');
-  const div  = document.createElement('div');
-  div.className = `log-line log-${level}`;
-  const ts = new Date().toLocaleTimeString('en-GB', { hour12: false });
-  div.textContent = `[${ts}] ${msg}`;
-  feed.appendChild(div);
-  feed.scrollTop = feed.scrollHeight;
-  // Max 200 lines
-  while (feed.children.length > 200) feed.removeChild(feed.firstChild);
-}
-
-// ── Phase indicator helpers ───────────────────────────────────────────────────
-
-function setPhaseActive(phase) {
-  const map = { setup: 'phase-setup', phase1: 'phase-phase1', phase2: 'phase-phase2', phase3: 'phase-phase3' };
-  const id  = map[phase];
-  if (!id) return;
-  document.querySelectorAll('.phase-step').forEach(s => s.classList.remove('active'));
-  const step = el(id);
-  if (step) step.classList.add('active');
-}
-
-function markPhaseDone(phase) {
-  const map = { phase1: 'phase-phase1', phase2: 'phase-phase2', phase3: 'phase-phase3', done: 'phase-done' };
-  const step = el(map[phase]);
-  if (step) { step.classList.remove('active'); step.classList.add('done'); }
-}
-
-// ── Status helpers ────────────────────────────────────────────────────────────
-
-function setStatus(state, phase) {
-  const dot   = el('state-dot');
-  const label = el('state-label');
-
-  const states = {
-    running:  { cls: 'dot-running', label: phase ? `${phase.replace('phase','Phase ')}` : 'Running' },
-    stopping: { cls: 'dot-warn',    label: 'Stopping...' },
-    idle:     { cls: 'dot-idle',    label: 'Ready' },
-    done:     { cls: 'dot-done',    label: 'Complete' },
-  };
-  const s = states[state] || states.idle;
-  dot.className   = `dot ${s.cls}`;
-  label.textContent = s.label;
-}
-
-function updateRunCount(count, d) {
-  if (count !== null) runCount = count;
-  else if (d) runCount++;
-  el('hdr-iter').textContent = totalRuns > 0 ? `${runCount}/${totalRuns}` : runCount;
-}
-
-function updatePhaseLabel(phase, runNum, total) {
-  const labels = { phase1: 'Phase 1: Broad Search', phase2: 'Phase 2: Refinement', phase3: 'Phase 3: Validation', phase3_oos: 'Phase 3: OOS Test', phase3_sens: 'Phase 3: Sensitivity' };
-  el('progress-phase').textContent = labels[phase] || phase;
-  if (runNum != null && total != null) {
-    el('progress-count').textContent = `${runNum} / ${total}`;
-    el('progress-bar-fill').style.width = `${Math.round(runNum / total * 100)}%`;
+  if (d.run_number !== undefined && d.total !== undefined) {
+    safe('opt-gen',       e => { e.textContent = 'Run ' + d.run_number + ' / ' + d.total; });
+    safe('hdr-gen-cur',   e => { e.textContent = d.run_number; });
+    safe('hdr-gen-total', e => { e.textContent = d.total; });
+    safe('opt-remaining', e => {
+      if (!state.startTime || !d.run_number) return;
+      const elapsed = (Date.now() - state.startTime) / 1000;
+      const rem = (elapsed / d.run_number) * (d.total - d.run_number);
+      e.textContent = fmtTime(rem);
+    });
   }
 }
 
-// ── Elapsed timer ─────────────────────────────────────────────────────────────
+/* ══════════════════════════════════════════════════════════════════════
+   ELAPSED TIMER
+══════════════════════════════════════════════════════════════════════ */
 
 function startElapsedTimer() {
-  if (elapsedTimer) clearInterval(elapsedTimer);
-  if (!startTs) startTs = Date.now();
-  elapsedTimer = setInterval(() => {
-    const secs = Math.floor((Date.now() - startTs) / 1000);
-    const mm   = Math.floor(secs / 60).toString().padStart(2, '0');
-    const ss   = (secs % 60).toString().padStart(2, '0');
-    el('hdr-elapsed').textContent = `${mm}:${ss}`;
+  if (!state.startTime) state.startTime = Date.now();
+  stopElapsedTimer();
+  state.elapsedTimer = setInterval(() => {
+    const secs = Math.floor((Date.now() - state.startTime) / 1000);
+    safe('opt-elapsed', e => { e.textContent = fmtTime(secs); });
   }, 1000);
 }
 
 function stopElapsedTimer() {
-  if (elapsedTimer) { clearInterval(elapsedTimer); elapsedTimer = null; }
+  if (state.elapsedTimer) { clearInterval(state.elapsedTimer); state.elapsedTimer = null; }
 }
 
-// ── Utility ───────────────────────────────────────────────────────────────────
+/* ══════════════════════════════════════════════════════════════════════
+   RUNNING STATE TOGGLE
+══════════════════════════════════════════════════════════════════════ */
 
-function el(id) { return document.getElementById(id); }
+function setRunningState(isRunning, label) {
+  state.isRunning = isRunning;
 
-// Init: mark Setup phase as active
-setPhaseActive('setup');
+  safe('run-indicator', e => { e.classList.toggle('active', isRunning); });
+  safe('btn-stop',  e => { e.classList.toggle('active', isRunning); });
+  // (btn-pause removed — pipeline doesn't support pause yet)
 
-// Check if run already in progress
-fetch('/api/status').then(r => r.json()).then(s => {
-  if (s.state === 'running') {
-    setStatus(s.state, s.phase);
-    startTs = Date.now() - (s.elapsed_s || 0) * 1000;
+  safe('hdr-dot',        e => { e.classList.toggle('running', isRunning); });
+  safe('hdr-status',     e => { e.textContent = isRunning ? (label || 'Optimizing') : 'System Idle'; });
+  safe('hdr-status-sub', e => { e.textContent = isRunning ? 'Optimization in progress...' : 'Ready to optimize'; });
+
+  if (isRunning) {
+    if (label) safe('run-indicator-label', e => { e.textContent = label; });
     startElapsedTimer();
-    totalRuns = s.total_runs || 0;
-    updateRunCount(s.run_count || 0, null);
-    document.getElementById('progress-wrap').style.display = '';
-    document.getElementById('btn-stop').classList.remove('hidden');
-    setPhaseActive(s.phase);
-    if (s.ea_name) {
-      document.getElementById('session-label').textContent =
-        `${s.ea_name} · ${s.symbol} · ${s.timeframe}`;
+  } else {
+    stopElapsedTimer();
+  }
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   PHASE STEPS
+══════════════════════════════════════════════════════════════════════ */
+
+const phaseMap = {
+  phase1: 1, phase_1: 1, broad: 1, scan: 1,
+  phase2: 2, phase_2: 2, deep: 2, refine: 2,
+  phase3: 3, phase_3: 3, validate: 3, validation: 3, phase3_oos: 3, phase3_sens: 3,
+};
+
+function setPhaseActive(phaseNum, meta) {
+  for (let i = 1; i <= 3; i++) {
+    const step = el('phase-step-' + i);
+    if (!step) continue;
+    step.classList.remove('active', 'done');
+    if (i < phaseNum) step.classList.add('done');
+    if (i === phaseNum) step.classList.add('active');
+  }
+  const labels = { 1: 'Exploration', 2: 'Iteration', 3: 'Validation' };
+  safe('opt-phase', e => { e.textContent = labels[phaseNum] || 'Phase ' + phaseNum; });
+  if (meta && typeof meta.total === 'number') {
+    const mode = meta.mode === 'autonomous' ? ' · AI' : '';
+    safe('phase-sub-' + phaseNum, e => {
+      e.textContent = `0/${meta.total}${mode}`;
+    });
+  }
+}
+
+function updatePhaseSubProgress(phaseNum, current, total) {
+  safe('phase-sub-' + phaseNum, e => {
+    e.textContent = `${current}/${total}`;
+  });
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   LIVE LOG
+══════════════════════════════════════════════════════════════════════ */
+
+const MAX_LOG_LINES = 200;
+
+function addLog(msg, level) {
+  const lvl = level || 'info';
+  state.logCount++;
+  safe('log-count', e => { e.textContent = state.logCount; });
+
+  const feed = el('log-feed');
+  if (!feed) return;
+
+  const line = document.createElement('div');
+  line.className = 'log-line ' + lvl;
+  line.innerHTML = '<span class="log-time">' + nowStr() + '</span><span class="log-msg">' + escapeHtml(String(msg)) + '</span>';
+  feed.appendChild(line);
+  while (feed.children.length > MAX_LOG_LINES) feed.removeChild(feed.firstChild);
+  feed.scrollTop = feed.scrollHeight;
+}
+
+function toggleLog() {
+  const body = el('log-body');
+  const icon = el('log-toggle-icon');
+  if (body) body.classList.toggle('open');
+  if (icon) icon.classList.toggle('open');
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   MT5 STATUS
+══════════════════════════════════════════════════════════════════════ */
+
+function updateMT5Status(statusStr, label) {
+  const dot = el('mt5-dot');
+  if (dot) dot.classList.toggle('disconnected', statusStr === 'disconnected');
+  safe('mt5-state', e => { e.textContent = label || statusStr; });
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   VERDICT OVERLAY
+══════════════════════════════════════════════════════════════════════ */
+
+function showVerdict(d) {
+  const icons   = { RECOMMENDED: '✅', RISKY: '⚠️', NOT_RELIABLE: '❌' };
+  const colors  = { RECOMMENDED: '#10b981', RISKY: '#f59e0b', NOT_RELIABLE: '#ef4444' };
+  const subs    = {
+    RECOMMENDED:  'Consistent returns with controlled drawdown. Ready to deploy.',
+    RISKY:        'Profitable in-sample but shows fragility. Deploy with caution.',
+    NOT_RELIABLE: 'Results are inconsistent. Try different settings or date ranges.',
+  };
+
+  const verdict = (d.verdict || 'RISKY').toUpperCase().replace(/ /g, '_');
+
+  safe('verdict-icon',     e => { e.textContent = icons[verdict] || '?'; });
+  safe('verdict-title',    e => { e.textContent = verdict.replace(/_/g, ' '); e.style.color = colors[verdict] || '#e2e8f0'; });
+  safe('verdict-subtitle', e => { e.textContent = subs[verdict] || ''; });
+
+  const profit  = parseFloat(d.net_profit  || 0);
+  const calmar  = parseFloat(d.calmar      || 0);
+  const winRate = parseFloat(d.win_rate    || 0);
+  const maxDD   = parseFloat(d.max_drawdown || d.max_dd || 0);
+
+  safe('verdict-metrics', e => {
+    e.innerHTML = `
+      <div class="vm"><div class="vm-val" style="color:#10b981">${fmtMoney(profit)}</div><div class="vm-lbl">Net Profit</div></div>
+      <div class="vm"><div class="vm-val">${calmar.toFixed(2)}</div><div class="vm-lbl">Calmar</div></div>
+      <div class="vm"><div class="vm-val">${winRate.toFixed(1)}%</div><div class="vm-lbl">Win Rate</div></div>
+      <div class="vm"><div class="vm-val" style="color:#ef4444">${maxDD.toFixed(1)}%</div><div class="vm-lbl">Max DD</div></div>
+    `;
+  });
+
+  safe('verdict-actions', e => {
+    e.innerHTML = `
+      ${d.set_file_url ? '<a href="' + d.set_file_url + '" class="verdict-btn primary" download>⬇ Download .set File</a>' : ''}
+      <a href="/reports" class="verdict-btn secondary">📋 View Report</a>
+      <a href="/setup"   class="verdict-btn secondary">⚡ New Run</a>
+      <button class="verdict-btn ghost" onclick="document.getElementById('verdict-overlay').style.display='none'">✕ Close</button>
+    `;
+  });
+
+  safe('verdict-overlay', e => { e.style.display = 'flex'; });
+  stopElapsedTimer();
+  setRunningState(false);
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   STATUS POLLING FALLBACK
+   Polls /api/status every 5 seconds when SocketIO is connected but
+   pipeline state is unknown (e.g., user opens dashboard mid-run).
+══════════════════════════════════════════════════════════════════════ */
+
+let pollInterval = null;
+
+function startPolling() {
+  if (pollInterval) return;
+  pollInterval = setInterval(async () => {
+    try {
+      const resp = await fetch('/api/status');
+      const d = await resp.json();
+      syncFromStatus(d);
+    } catch (_) {}
+  }, 5000);
+}
+
+function stopPolling() {
+  if (pollInterval) { clearInterval(pollInterval); pollInterval = null; }
+}
+
+function syncFromStatus(d) {
+  const isRunning = d.state === 'running';
+
+  if (isRunning && !state.isRunning) {
+    setRunningState(true, d.phase || 'Optimizing...');
+    const ph = phaseMap[d.phase] || 1;
+    setPhaseActive(ph);
+  } else if (!isRunning && state.isRunning) {
+    setRunningState(false);
+  }
+
+  if (d.run_count) {
+    state.runs = d.run_count;
+    safe('m-runs', e => { e.textContent = state.runs.toString(); });
+  }
+
+  // Populate metric cards from flat status fields
+  if (d.best_net_profit != null || d.best_max_drawdown != null) {
+    updateMetricCards({
+      net_profit:    d.best_net_profit,
+      max_drawdown:  d.best_max_drawdown,
+      profit_factor: d.best_pf,
+      total_trades:  d.best_total_trades,
+    });
+  }
+
+  // Restore header score
+  if (d.best_score != null) updateHeaderScore(d.best_score);
+
+  // Restore AI panel
+  if (d.latest_insight) {
+    updateAIPanel(d.latest_insight);
+    addLog('AI insight restored from server (run: ' + (d.latest_insight.run_id || '?') + ')', 'info');
+  }
+
+  if (d.elapsed_s) {
+    // Approximate startTime from elapsed
+    if (!state.startTime) state.startTime = Date.now() - d.elapsed_s * 1000;
+  }
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   SOCKET.IO
+══════════════════════════════════════════════════════════════════════ */
+
+const socket = io({ transports: ['websocket', 'polling'] });
+if (typeof window !== 'undefined') window.socket = socket;
+
+socket.on('connect', () => {
+  addLog('Connected to APEX server.', 'success');
+  updateMT5Status('connected', 'Connected');
+  // Also poll once to sync state immediately
+  fetch('/api/status').then(r => r.json()).then(syncFromStatus).catch(() => {});
+});
+
+socket.on('disconnect', (reason) => {
+  addLog('Disconnected: ' + reason, 'warn');
+  updateMT5Status('disconnected', 'Disconnected');
+});
+
+socket.on('connect_error', (err) => {
+  addLog('Connection error: ' + err.message, 'error');
+  updateMT5Status('disconnected', 'Error');
+});
+
+/* ── status_sync ── full state on reconnect ───────────────────────── */
+
+socket.on('status_sync', (d) => {
+  addLog('Status sync received.', 'info');
+  syncFromStatus(d);
+});
+
+/* ── status_change ────────────────────────────────────────────────── */
+
+socket.on('status_change', (d) => {
+  // Backend emits d.state NOT d.status
+  const running = d.state === 'running' || d.status === 'running';
+  const label = d.label || d.phase || (running ? 'Optimizing...' : 'Idle');
+  setRunningState(running, label);
+  addLog('Status: ' + (d.state || d.status || (running ? 'running' : 'idle')), 'info');
+
+  // Reset live-intelligence panels when a fresh run starts
+  if (running && (d.state === 'running' || d.status === 'running') && d.phase === 'setup') {
+    thinkingFeedState.entries = [];
+    paramChangesState.iterations = [];
+    validationState.runs = [];
+    validationState.planned = 0;
+    validationState.complete = 0;
+    validationState.active = false;
+    renderThinkingFeed();
+    renderParamChanges();
+    renderValidation();
+    safe('tf-badge', e => { e.textContent = 'Live'; e.className = 'badge live'; });
+    safe('pc-badge', e => { e.textContent = '—'; e.className = 'badge'; });
+    safe('val-badge', e => { e.textContent = 'Pending'; e.className = 'badge'; });
+    dismissEarlyTerm();
+  }
+});
+
+/* ── run_complete ─────────────────────────────────────────────────── */
+
+socket.on('run_complete', (d) => {
+  updateRunsCounter();
+
+  // Only update metric cards if we have meaningful data
+  if (d.net_profit != null) updateMetricCards(d);
+
+  // Charts: use equity curve if available, otherwise push single point
+  if (d.equity_curve) {
+    populateChartsFromEquityCurve(d.equity_curve);
+  } else if (d.net_profit != null) {
+    pushEquityPoint(d.net_profit, d.balance || d.net_profit, 'Run ' + state.runs);
+    pushDDPoint(d.max_drawdown || 0, 'Run ' + state.runs);
+  }
+
+  if (d.params) updateParamsTable(d.params);
+  if (d.score != null) updateHeaderScore(d.score);
+
+  addRecentRun(d);
+  updateProgress(d);
+
+  // Update per-phase sub-progress label under phase dot
+  const phase = (d.phase || '').toLowerCase();
+  if (phase === 'phase1' && d.run_number && d.total) {
+    updatePhaseSubProgress(1, d.run_number, d.total);
+  } else if (phase.startsWith('phase2') && d.progress_pct != null) {
+    // Rough count: we don't always have iteration here; UI updates via ai_iteration_* handler
+  } else if (phase.startsWith('phase3')) {
+    // Updated via validation_run_complete handler
+  }
+
+  const msg = 'Run ' + state.runs + ' (' + (d.phase || '?') + ') '
+    + (d.net_profit != null ? '— Net Profit: ' + fmtMoney(d.net_profit) : '')
+    + (d.profit_factor != null ? ', PF: ' + parseFloat(d.profit_factor).toFixed(2) : '')
+    + (d.max_drawdown != null ? ', Max DD: ' + fmtPct(d.max_drawdown) : '');
+  addLog(msg, d.passing === false ? 'warn' : 'success');
+});
+
+/* ── phase_start ──────────────────────────────────────────────────── */
+
+socket.on('phase_start', (d) => {
+  const phaseNum = phaseMap[d.phase] || parseInt(d.phase_num || d.phase || '1', 10);
+  setPhaseActive(phaseNum, { total: d.total, mode: d.mode });
+  const label = d.label
+    || ({ 1: 'Exploration', 2: (d.mode === 'autonomous' ? 'AI Iteration' : 'Iteration'), 3: 'Validation' }[phaseNum])
+    || ('Phase ' + phaseNum);
+  addLog('Phase started: ' + label, 'info');
+  safe('run-indicator-label', e => { e.textContent = label + '...'; });
+  setRunningState(true, label);
+});
+
+/* ── phase1_complete ──────────────────────────────────────────────── */
+
+socket.on('phase1_complete', (d) => {
+  addLog('Phase 1 complete — ' + (d.n_passing || 0) + '/' + (d.total_tested || '?') + ' configs passed.', 'success');
+  setPhaseActive(2);
+
+  // Backend emits top_results (NOT top_configs)
+  const topResults = d.top_results || d.top_configs || [];
+  if (topResults.length) {
+    if (topResults[0] && topResults[0].params) updateParamsTable(topResults[0].params);
+    topResults.forEach(cfg => addRecentRun(cfg));
+  }
+});
+
+/* ── phase2_complete ──────────────────────────────────────────────── */
+
+socket.on('phase2_complete', (d) => {
+  addLog('Phase 2 complete — best: ' + (d.best_run_id || '?') + ', profit=$' + (d.best_profit || 0), 'success');
+  setPhaseActive(3);
+
+  // Phase2 complete has flat fields: best_profit, best_calmar
+  if (d.best_profit != null) {
+    updateMetricCards({ net_profit: d.best_profit, calmar: d.best_calmar });
+  }
+});
+
+/* ── optimization_complete ────────────────────────────────────────── */
+
+socket.on('optimization_complete', (d) => {
+  addLog('✅ Optimization complete! Verdict: ' + (d.verdict || '?'), 'success');
+  for (let i = 1; i <= 3; i++) {
+    const step = el('phase-step-' + i);
+    if (step) { step.classList.remove('active'); step.classList.add('done'); }
+  }
+  safe('opt-progress-fill', e => { e.style.width = '100%'; });
+  safe('hdr-prog-fill',     e => { e.style.width = '100%'; });
+  safe('hdr-pct',           e => { e.textContent = '100% Complete'; });
+  safe('opt-phase', e => { e.textContent = 'Complete'; });
+  if (d.score != null) updateHeaderScore(d.score);
+  showVerdict(d);
+});
+
+/* ── ai_insight ───────────────────────────────────────────────────── */
+
+socket.on('ai_insight', (d) => {
+  updateAIPanel(d);
+  addLog('AI Insight received (confidence: ' + (d.confidence || '?') + ')', 'info');
+});
+
+/* ── log ──────────────────────────────────────────────────────────── */
+
+socket.on('log', (d) => {
+  const msg   = typeof d === 'string' ? d : (d.msg || d.message || JSON.stringify(d));
+  const level = typeof d === 'object' ? (d.level || 'info') : 'info';
+  addLog(msg, level);
+});
+
+/* ── no_profitable_config ─────────────────────────────────────────── */
+
+socket.on('no_profitable_config', (d) => {
+  safe('no-profit-banner', e => {
+    e.classList.add('active');
+    // Backend emits d.msg (not d.message)
+    const text = (d && (d.msg || d.message)) || 'No profitable configuration found.';
+    const msgEl = el('no-profit-msg');
+    if (msgEl) msgEl.textContent = ' ' + text;
+  });
+  setRunningState(false);
+  addLog('No profitable configuration found.', 'warn');
+});
+
+/* ── error ────────────────────────────────────────────────────────── */
+
+socket.on('error', (d) => {
+  const msg = (d && d.msg) || 'Unknown server error';
+  addLog('Server error: ' + msg, 'error');
+  setRunningState(false);
+});
+
+/* ── Autonomous AI Loop events ─────────────────────────────────────── */
+
+socket.on('ai_iteration_start', (d) => {
+  const iter = d.iteration || '?';
+  const max  = d.max_iterations || '?';
+  safe('hdr-status',     e => { e.textContent = 'AI Loop'; });
+  safe('hdr-status-sub', e => { e.textContent = `Iteration ${iter} / ${max}`; });
+
+  let msg = `🤖 AI Iteration ${iter}/${max}`;
+  if (d.is_stuck_escape) {
+    msg += ' [escape mode]';
+  } else if (d.changes && d.changes.length) {
+    const changes = d.changes.map(c => `${c.param}=${c.value}`).join(', ');
+    msg += ` — trying: ${changes}`;
+  }
+  addLog(msg, 'info');
+  if (d.analysis) addLog(`  AI reasoning: ${d.analysis}`, 'info');
+});
+
+socket.on('ai_iteration_complete', (d) => {
+  const iter   = d.iteration || '?';
+  const max    = d.max_iterations || 0;
+  const pf     = parseFloat(d.profit_factor || 0).toFixed(2);
+  const calmar = parseFloat(d.calmar || 0).toFixed(2);
+  const dd     = parseFloat(d.max_drawdown || 0).toFixed(1);
+  const status = d.passing ? '✅' : '❌';
+
+  addLog(
+    `  ${status} iter=${iter} | PF=${pf} | Calmar=${calmar} | DD=${dd}% | `
+    + `confidence=${(d.confidence || 0).toFixed(2)}`,
+    d.passing ? 'success' : 'warn'
+  );
+
+  if (typeof iter === 'number' && max) updatePhaseSubProgress(2, iter, max);
+  if (d.best_score != null) updateHeaderScore(d.best_score);
+
+  if (d.goal_status) {
+    const gs = d.goal_status;
+    const flags = [
+      gs.profit_factor_met ? '✓ PF'     : '✗ PF',
+      gs.drawdown_ok       ? '✓ DD'     : '✗ DD',
+      gs.calmar_met        ? '✓ Calmar' : '✗ Calmar',
+    ].join('  ');
+    addLog(`  Targets: ${flags}`, 'info');
+  }
+
+  if (d.targets_met) addLog('🎯 All targets met! Stopping AI loop early.', 'success');
+});
+
+socket.on('ai_targets_met', (d) => {
+  addLog(
+    `🎯 Targets achieved after ${d.iteration} iterations — `
+    + `PF=${parseFloat(d.profit_factor || 0).toFixed(2)}, `
+    + `Calmar=${parseFloat(d.calmar || 0).toFixed(2)}, `
+    + `DD=${parseFloat(d.max_drawdown || 0).toFixed(1)}%`,
+    'success'
+  );
+});
+
+socket.on('ai_stuck', (d) => {
+  addLog(`⚠ AI loop stuck at iteration ${d.iteration} — applying random escape`, 'warn');
+});
+
+/* ══════════════════════════════════════════════════════════════════════
+   LIVE INTELLIGENCE — AI Thinking Feed / Param Changes / Validation
+══════════════════════════════════════════════════════════════════════ */
+
+const MAX_THINKING_ENTRIES = 150;
+const MAX_PARAM_CHANGE_ITERATIONS = 20;
+const thinkingFeedState = { entries: [], active: false };
+const paramChangesState = { iterations: [] };
+const validationState   = { runs: [], planned: 0, complete: 0, active: false };
+
+function _formatVal(v) {
+  if (v === null || v === undefined) return '—';
+  if (typeof v === 'number') {
+    if (Number.isInteger(v)) return String(v);
+    return Number(v).toFixed(Math.abs(v) < 10 ? 4 : 2);
+  }
+  return String(v);
+}
+
+function _markerFor(kind) {
+  return {
+    info:       '•',
+    reasoning:  '✦',
+    decision:   '→',
+    success:    '✓',
+    warning:    '⚠',
+    hypothesis: '?',
+  }[kind] || '•';
+}
+
+function renderThinkingFeed() {
+  const box = el('thinking-feed');
+  if (!box) return;
+  if (!thinkingFeedState.entries.length) {
+    box.innerHTML = '<div class="live-intel-empty">Waiting for the optimizer to start…<br><span style="font-size:0.68rem">The AI\'s reasoning will stream here in real time.</span></div>';
+    return;
+  }
+  box.innerHTML = thinkingFeedState.entries.map(e => {
+    const kind = e.kind || 'info';
+    const iter = e.iteration ? `<span class="tf-chip">iter ${e.iteration}</span>` : '';
+    const phase = e.phase ? `<span class="tf-chip">${escapeHtml(e.phase)}</span>` : '';
+    const time = e.time ? `<span>${escapeHtml(e.time)}</span>` : '';
+    return `<div class="tf-entry ${kind}">
+      <div class="tf-marker">${_markerFor(kind)}</div>
+      <div class="tf-body">
+        <div class="tf-msg">${escapeHtml(e.msg)}</div>
+        <div class="tf-meta">${time}${iter}${phase}</div>
+      </div>
+    </div>`;
+  }).join('');
+  // Auto-scroll to bottom so latest entry is visible
+  box.scrollTop = box.scrollHeight;
+}
+
+function addThinking(d) {
+  const entry = {
+    msg:       d.msg || '',
+    kind:      d.kind || 'info',
+    iteration: d.iteration,
+    phase:     d.phase,
+    time:      nowStr(),
+  };
+  thinkingFeedState.entries.push(entry);
+  if (thinkingFeedState.entries.length > MAX_THINKING_ENTRIES) {
+    thinkingFeedState.entries.shift();
+  }
+  thinkingFeedState.active = true;
+  safe('tf-badge', e => { e.textContent = 'Live'; e.className = 'badge live'; });
+  renderThinkingFeed();
+}
+
+function renderParamChanges() {
+  const box = el('param-changes-list');
+  if (!box) return;
+  if (!paramChangesState.iterations.length) {
+    box.innerHTML = '<div class="live-intel-empty">No iterations yet.<br><span style="font-size:0.68rem">AI-driven parameter edits appear per iteration.</span></div>';
+    return;
+  }
+  // Newest first
+  const items = [...paramChangesState.iterations].reverse();
+  box.innerHTML = items.map(it => {
+    const changes = (it.changes || []).map(c => `
+      <div class="pc-change">
+        <span class="pc-param">${escapeHtml(c.param || '')}</span>:
+        <span class="pc-oldval">${escapeHtml(_formatVal(c.from))}</span>
+        <span class="pc-arrow">→</span>
+        <span class="pc-newval">${escapeHtml(_formatVal(c.to))}</span>
+        ${c.reason ? `<div class="pc-reason">${escapeHtml(c.reason)}</div>` : ''}
+      </div>
+    `).join('');
+    const conf = (typeof it.confidence === 'number')
+      ? `conf ${(it.confidence * 100).toFixed(0)}%`
+      : '';
+    return `<div class="pc-iteration">
+      <div class="pc-iter-header">
+        <span class="pc-iter-label">iter ${it.iteration}</span>
+        <span class="pc-iter-conf">${escapeHtml(conf)}</span>
+      </div>
+      ${changes || '<div class="pc-change" style="color:var(--muted);font-style:italic">(no param changes — random escape)</div>'}
+    </div>`;
+  }).join('');
+}
+
+function addParamChanges(d) {
+  paramChangesState.iterations.push({
+    iteration:  d.iteration,
+    changes:    d.changes || d.change_records || [],
+    analysis:   d.analysis || '',
+    confidence: d.confidence,
+  });
+  if (paramChangesState.iterations.length > MAX_PARAM_CHANGE_ITERATIONS) {
+    paramChangesState.iterations.shift();
+  }
+  safe('pc-badge', e => { e.textContent = `iter ${d.iteration}`; e.className = 'badge live'; });
+  renderParamChanges();
+}
+
+function renderValidation() {
+  const box = el('validation-panel');
+  if (!box) return;
+  if (!validationState.active && !validationState.runs.length) {
+    box.innerHTML = '<div class="live-intel-empty">Validation runs after optimization.<br><span style="font-size:0.68rem">Out-of-sample + sensitivity tests.</span></div>';
+    return;
+  }
+  const planned = validationState.planned || validationState.runs.length;
+  const done    = validationState.complete;
+  const pct     = planned > 0 ? Math.round(done / planned * 100) : 0;
+  const progress = `
+    <div class="val-progress-row">
+      <span>${done}/${planned}</span>
+      <div class="val-progress-bar"><div class="val-progress-fill" style="width:${pct}%"></div></div>
+      <span>${pct}%</span>
+    </div>`;
+  const runsHtml = validationState.runs.map(r => {
+    let clsExtra = r.status === 'running' ? 'active' : (r.passing === true ? 'pass' : (r.passing === false ? 'fail' : ''));
+    const statusBadge = r.status === 'running'
+      ? '<span class="val-spinner"></span>'
+      : (r.passing ? '<span style="color:var(--green)">✓</span>'
+                   : r.passing === false ? '<span style="color:var(--red)">✗</span>' : '');
+    const metrics = (r.status === 'complete') ? `
+      <div class="val-run-metrics">
+        <div class="val-metric"><div class="val-metric-lbl">Profit</div><div class="val-metric-val" style="color:${r.net_profit >= 0 ? 'var(--green)' : 'var(--red)'}">${fmtMoney(r.net_profit)}</div></div>
+        <div class="val-metric"><div class="val-metric-lbl">PF</div><div class="val-metric-val" style="color:var(--yellow)">${Number(r.profit_factor || 0).toFixed(2)}</div></div>
+        <div class="val-metric"><div class="val-metric-lbl">Calmar</div><div class="val-metric-val" style="color:var(--teal)">${Number(r.calmar || 0).toFixed(2)}</div></div>
+        <div class="val-metric"><div class="val-metric-lbl">DD</div><div class="val-metric-val" style="color:var(--red)">${Number(r.max_drawdown || 0).toFixed(1)}%</div></div>
+      </div>` : '';
+    return `<div class="val-run ${clsExtra}">
+      <div class="val-run-title">
+        ${statusBadge}
+        <span>${escapeHtml(r.label || r.kind || 'Run')}</span>
+        <span class="val-run-kind ${escapeHtml(r.kind || '')}">${escapeHtml(r.kind || '')}</span>
+      </div>
+      ${r.description ? `<div class="val-run-desc">${escapeHtml(r.description)}</div>` : ''}
+      ${metrics}
+    </div>`;
+  }).join('');
+  box.innerHTML = progress + runsHtml;
+}
+
+function validationRunStart(d) {
+  validationState.active = true;
+  validationState.planned = d.total || validationState.planned;
+  // Replace any existing run with same run_id
+  validationState.runs = validationState.runs.filter(r => r.run_id !== d.run_id);
+  validationState.runs.push({
+    run_id:      d.run_id,
+    kind:        d.kind,
+    label:       d.label,
+    description: d.description,
+    index:       d.index,
+    status:      'running',
+  });
+  safe('val-badge', e => { e.textContent = `Running ${d.index}/${d.total || validationState.planned}`; e.className = 'badge live'; });
+  renderValidation();
+}
+
+function validationRunComplete(d) {
+  const idx = validationState.runs.findIndex(r => r.run_id === d.run_id);
+  const base = idx >= 0 ? validationState.runs[idx] : { run_id: d.run_id, kind: d.kind, label: d.label };
+  const merged = {
+    ...base,
+    status:        'complete',
+    net_profit:    d.net_profit,
+    profit_factor: d.profit_factor,
+    calmar:        d.calmar,
+    max_drawdown:  d.max_drawdown,
+    total_trades:  d.total_trades,
+    passing:       d.passing,
+  };
+  if (idx >= 0) validationState.runs[idx] = merged;
+  else validationState.runs.push(merged);
+  validationState.complete++;
+  renderValidation();
+}
+
+function validationDone(d) {
+  validationState.active = false;
+  const label = ({
+    RECOMMENDED:  'Passed',
+    RISKY:        'Mixed',
+    NOT_RELIABLE: 'Failed',
+  })[d.verdict] || 'Done';
+  const cls = d.verdict === 'RECOMMENDED' ? 'live' : '';
+  safe('val-badge', e => { e.textContent = label; e.className = `badge ${cls}`; });
+  renderValidation();
+}
+
+function showEarlyTermination(d) {
+  const banner = el('early-term-banner');
+  if (!banner) return;
+  const reason = d.reason || 'unknown';
+  const cls = {
+    targets_met:       'success',
+    no_profit:         'critical',
+    budget_exhausted:  'warning',
+    stuck_escape:      'warning',
+    user_stop:         'warning',
+  }[reason] || 'warning';
+  banner.className = `early-term-banner ${cls} active`;
+
+  const icon = {
+    targets_met: '🎯',
+    no_profit:   '⚠',
+    budget_exhausted: '⏱',
+    stuck_escape: '↻',
+    user_stop: '⏹',
+  }[reason] || '⚠';
+  safe('early-term-icon', e => { e.textContent = icon; });
+
+  const heading = {
+    targets_met:      'Targets Met — Optimization Complete',
+    no_profit:        'Optimization Stopped Early',
+    budget_exhausted: 'Time Budget Exhausted',
+    stuck_escape:     'Optimizer Stuck',
+    user_stop:        'Stopped by User',
+  }[reason] || 'Optimization Event';
+  safe('early-term-heading', e => { e.textContent = heading; });
+
+  safe('early-term-msg', e => { e.textContent = d.message || ''; });
+
+  // Render details as chips
+  const det = d.details || {};
+  const chips = Object.entries(det)
+    .filter(([k, v]) => typeof v !== 'object' && v !== null && v !== undefined && v !== '')
+    .map(([k, v]) => `<span>${escapeHtml(k)}: <strong style="color:var(--text)">${escapeHtml(String(v))}</strong></span>`)
+    .join('');
+  safe('early-term-details', e => { e.innerHTML = chips; });
+}
+
+function dismissEarlyTerm() {
+  safe('early-term-banner', e => { e.classList.remove('active'); });
+}
+
+/* ── Socket wiring for new events ─────────────────────────────────── */
+
+socket.on('ai_thinking', (d) => {
+  addThinking(d);
+});
+
+socket.on('param_changes', (d) => {
+  addParamChanges(d);
+});
+
+socket.on('validation_start', (d) => {
+  // Reset the panel for a fresh validation phase
+  validationState.runs = [];
+  validationState.planned = d.planned_runs || 0;
+  validationState.complete = 0;
+  validationState.active = true;
+  safe('val-badge', e => { e.textContent = `0/${d.planned_runs}`; e.className = 'badge live'; });
+  renderValidation();
+  addLog(`Validation: planning ${d.planned_runs} test runs`, 'info');
+});
+
+socket.on('validation_run_start', (d) => {
+  validationRunStart(d);
+});
+
+socket.on('validation_run_complete', (d) => {
+  validationRunComplete(d);
+});
+
+socket.on('validation_done', (d) => {
+  validationDone(d);
+});
+
+socket.on('early_termination', (d) => {
+  showEarlyTermination(d);
+  addLog(`⚠ ${d.message}`, d.reason === 'targets_met' ? 'success' : 'warn');
+});
+
+/* ── Also capture change_records from ai_iteration_start as a fallback ── */
+socket.on('ai_iteration_start', (d) => {
+  // (existing handler runs first — this just ensures param-changes panel is populated
+  //  even if the dedicated param_changes event is missed for any reason)
+  if (d.change_records && d.change_records.length) {
+    const already = paramChangesState.iterations.find(i => i.iteration === d.iteration);
+    if (!already) {
+      addParamChanges({
+        iteration:  d.iteration,
+        changes:    d.change_records,
+        analysis:   d.analysis,
+        confidence: d.confidence,
+      });
     }
   }
-}).catch(() => {});
+});
+
+/* ══════════════════════════════════════════════════════════════════════
+   STOP BUTTON — uses HTTP POST, not socket emit
+══════════════════════════════════════════════════════════════════════ */
+
+safe('btn-stop', stopBtn => {
+  stopBtn.addEventListener('click', async () => {
+    addLog('Stopping optimization...', 'warn');
+    stopBtn.classList.remove('active');
+    try {
+      await fetch('/api/stop', { method: 'POST' });
+      setRunningState(false);
+      addLog('Stop signal sent.', 'warn');
+    } catch (e) {
+      addLog('Stop request failed: ' + e.message, 'error');
+    }
+  });
+});
+
+/* Pause button removed — see dashboard.html. Pipeline only supports Stop. */
+
+/* ══════════════════════════════════════════════════════════════════════
+   HISTORY RESTORATION
+   Loads past runs from /api/history and /api/ai_insight/latest so
+   reopening the dashboard shows progressive data, not a blank slate.
+══════════════════════════════════════════════════════════════════════ */
+
+async function restoreHistory() {
+  try {
+    const [histResp, aiResp] = await Promise.all([
+      fetch('/api/history'),
+      fetch('/api/ai_insight/latest'),
+    ]);
+
+    const runs = await histResp.json();
+    if (Array.isArray(runs) && runs.length) {
+      // Populate recent runs table (last 8, newest first)
+      const sorted = runs.slice().reverse();
+      state.runs = runs.length;
+      safe('m-runs', e => { e.textContent = state.runs; });
+
+      sorted.slice(0, 8).forEach(r => addRecentRun(r));
+
+      // Push equity sparkline from net profits
+      runs.forEach(r => {
+        if (r.net_profit != null) {
+          pushEquityPoint(r.net_profit, r.net_profit, r.run_id || '');
+          pushDDPoint(r.max_drawdown || 0, r.run_id || '');
+          pushSparkData('profit', r.net_profit);
+          pushSparkData('dd', r.max_drawdown || 0);
+          pushSparkData('pf', r.profit_factor || 0);
+          pushSparkData('trades', r.total_trades || 0);
+          pushSparkData('runs', state.runs);
+        }
+      });
+
+      // Show best metrics
+      const passing = runs.filter(r => r.passing);
+      if (passing.length) {
+        const best = passing.reduce((a, b) => (a.net_profit > b.net_profit ? a : b));
+        updateMetricCards(best);
+        addLog('Restored ' + runs.length + ' past runs from history.', 'info');
+      }
+    }
+
+    // Restore AI panel if insight exists
+    const insight = await aiResp.json();
+    if (insight) {
+      updateAIPanel(insight);
+      addLog('AI insight restored (run: ' + (insight.run_id || '?') + ').', 'info');
+    }
+  } catch (e) {
+    addLog('History restore: ' + e.message, 'warn');
+  }
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   SETTINGS MODAL
+══════════════════════════════════════════════════════════════════════ */
+
+function openSettings() {
+  safe('settings-overlay', e => { e.style.display = 'flex'; });
+  loadSettings();
+}
+
+function closeSettings() {
+  safe('settings-overlay', e => { e.style.display = 'none'; });
+}
+
+function switchSettingsTab(tab) {
+  document.querySelectorAll('.settings-tab').forEach(t => {
+    t.classList.toggle('active', t.dataset.tab === tab);
+  });
+  document.querySelectorAll('.settings-panel').forEach(p => {
+    p.classList.toggle('active', p.id === 'stab-' + tab);
+  });
+}
+
+function toggleSettingsBool(btn) {
+  btn.classList.toggle('on');
+}
+
+function setBoolToggle(id, value) {
+  const btn = el(id);
+  if (!btn) return;
+  btn.classList.toggle('on', !!value);
+}
+
+function getBoolToggle(id) {
+  const btn = el(id);
+  return btn ? btn.classList.contains('on') : false;
+}
+
+function setVal(id, value) {
+  const e = el(id);
+  if (e) e.value = value != null ? value : '';
+}
+
+function getVal(id) {
+  const e = el(id);
+  return e ? e.value : '';
+}
+
+async function loadSettings() {
+  try {
+    const resp = await fetch('/api/settings');
+    const cfg = await resp.json();
+
+    // AI tab
+    setBoolToggle('s-ai-enabled', cfg.ai && cfg.ai.enabled !== false);
+    setVal('s-ai-key', (cfg.ai && cfg.ai.anthropic_api_key) || '');
+    setVal('s-ai-model', (cfg.ai && cfg.ai.model) || 'claude-opus-4-7');
+    setVal('s-ai-timeout', (cfg.ai && cfg.ai.timeout_seconds) || 30);
+
+    // MT5 tab
+    setVal('s-mt5-exe',     (cfg.mt5 && cfg.mt5.terminal_exe) || '');
+    setVal('s-mt5-appdata', (cfg.mt5 && cfg.mt5.appdata_path) || '');
+    setVal('s-mt5-mql5',   (cfg.mt5 && cfg.mt5.mql5_files_path) || '');
+    setVal('s-mt5-timeout', (cfg.mt5 && cfg.mt5.tester_timeout_seconds) || 120);
+    setVal('s-mt5-model',   (cfg.mt5 && cfg.mt5.tester_model) || 1);
+
+    // Broker tab
+    setVal('s-broker-tz',      (cfg.broker && cfg.broker.timezone_offset_hours) != null ? cfg.broker.timezone_offset_hours : 3);
+    setVal('s-broker-deposit',  (cfg.broker && cfg.broker.deposit) || 10000);
+    setVal('s-broker-leverage', (cfg.broker && cfg.broker.leverage) || 500);
+
+    // Thresholds tab
+    setVal('s-thr-trades',  (cfg.thresholds && cfg.thresholds.min_trades) || 30);
+    setVal('s-thr-pf',      (cfg.thresholds && cfg.thresholds.min_profit_factor) || 1.2);
+    setVal('s-thr-calmar',  (cfg.thresholds && cfg.thresholds.min_calmar) || 0.5);
+    setVal('s-thr-oos',     (cfg.thresholds && cfg.thresholds.max_oos_degradation) || 0.3);
+    setVal('s-thr-sens',    (cfg.thresholds && cfg.thresholds.sensitivity_tolerance) || 0.15);
+  } catch (e) {
+    showSettingsMsg('Failed to load settings: ' + e.message, false);
+  }
+}
+
+async function saveSettings() {
+  const btn = el('settings-save-btn');
+  if (btn) { btn.disabled = true; btn.textContent = 'Saving…'; }
+
+  const payload = {
+    ai: {
+      enabled:           getBoolToggle('s-ai-enabled'),
+      anthropic_api_key: getVal('s-ai-key').trim(),
+      model:             getVal('s-ai-model'),
+      timeout_seconds:   parseFloat(getVal('s-ai-timeout')) || 30,
+    },
+    mt5: {
+      terminal_exe:           getVal('s-mt5-exe').trim(),
+      appdata_path:           getVal('s-mt5-appdata').trim(),
+      mql5_files_path:        getVal('s-mt5-mql5').trim(),
+      tester_timeout_seconds: parseInt(getVal('s-mt5-timeout'), 10) || 120,
+      tester_model:           parseInt(getVal('s-mt5-model'), 10) || 1,
+    },
+    broker: {
+      timezone_offset_hours: parseFloat(getVal('s-broker-tz')) || 3,
+      deposit:               parseFloat(getVal('s-broker-deposit')) || 10000,
+      leverage:              parseInt(getVal('s-broker-leverage'), 10) || 500,
+    },
+    thresholds: {
+      min_trades:            parseInt(getVal('s-thr-trades'), 10) || 30,
+      min_profit_factor:     parseFloat(getVal('s-thr-pf')) || 1.2,
+      min_calmar:            parseFloat(getVal('s-thr-calmar')) || 0.5,
+      max_oos_degradation:   parseFloat(getVal('s-thr-oos')) || 0.3,
+      sensitivity_tolerance: parseFloat(getVal('s-thr-sens')) || 0.15,
+    },
+  };
+
+  try {
+    const resp = await fetch('/api/settings', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify(payload),
+    });
+    const data = await resp.json();
+    if (data.ok) {
+      showSettingsMsg('Settings saved.', true);
+      addLog('Settings saved successfully.', 'success');
+      setTimeout(closeSettings, 1200);
+    } else {
+      showSettingsMsg('Error: ' + (data.error || 'Unknown error'), false);
+    }
+  } catch (e) {
+    showSettingsMsg('Save failed: ' + e.message, false);
+  } finally {
+    if (btn) { btn.disabled = false; btn.textContent = 'Save Settings'; }
+  }
+}
+
+function showSettingsMsg(msg, ok) {
+  safe('settings-save-msg', e => {
+    e.textContent = msg;
+    e.className = 'settings-save-msg ' + (ok ? 'ok' : 'err');
+    e.style.opacity = '1';
+    setTimeout(() => { e.style.opacity = '0'; }, 3000);
+  });
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   AI PANEL TOGGLE
+══════════════════════════════════════════════════════════════════════ */
+
+function toggleAIDetails() {
+  const details = el('ai-details');
+  if (!details) return;
+  const isOpen = details.classList.contains('open');
+  details.classList.toggle('open', !isOpen);
+  const label = isOpen ? 'View Details →' : '▲ Collapse';
+  safe('ai-expand-btn',  e => { e.textContent = label; });
+  safe('ai-view-details', e => { e.textContent = label; });
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   RUN DETAIL MODAL
+══════════════════════════════════════════════════════════════════════ */
+
+async function openRunDetail(run_id) {
+  if (!run_id) return;
+
+  // Show modal immediately with loading state
+  safe('run-detail-overlay', e => { e.style.display = 'flex'; });
+  safe('rd-run-id',       e => { e.textContent = run_id; });
+  safe('rd-meta',         e => { e.textContent = 'Loading…'; });
+  safe('rd-metrics',      e => { e.innerHTML = ''; });
+  safe('rd-params-tbody', e => { e.innerHTML = '<tr><td colspan="2" class="empty-state">Loading…</td></tr>'; });
+  safe('rd-ai-section',   e => { e.style.display = 'none'; });
+  safe('rd-footer',       e => { e.innerHTML = '<button class="verdict-btn ghost" onclick="closeRunDetail()">Close</button>'; });
+  // Clear any lingering evolution section from a previous openBestResult call
+  const existingEvo = document.getElementById('rd-evolution-section');
+  if (existingEvo) existingEvo.remove();
+
+  try {
+    const resp = await fetch('/api/run/' + encodeURIComponent(run_id));
+    if (!resp.ok) throw new Error('HTTP ' + resp.status);
+    const d = await resp.json();
+
+    // Header
+    safe('rd-run-id', e => { e.textContent = d.run_id || run_id; });
+    const phase = (d.phase || '—').replace(/_/g, ' ');
+    const ts    = d.ts ? new Date(d.ts).toLocaleString() : '—';
+    safe('rd-meta', e => { e.textContent = 'Phase: ' + phase + '  ·  ' + ts; });
+
+    // Metrics grid
+    const profit = parseFloat(d.net_profit     || 0);
+    const pf     = parseFloat(d.profit_factor  || 0);
+    const calmar = parseFloat(d.calmar         || 0);
+    const dd     = parseFloat(d.drawdown_pct   || d.max_drawdown || 0);
+    const wr     = parseFloat(d.win_rate       || 0);
+    const trades = parseInt(d.total_trades     || 0, 10);
+    const score  = parseFloat(d.score          || 0);
+
+    const metrics = [
+      { label: 'Net Profit',    val: fmtMoney(profit),          color: profit >= 0 ? 'var(--green)' : 'var(--red)' },
+      { label: 'Profit Factor', val: pf.toFixed(2),             color: pf >= 1.5 ? 'var(--green)' : pf >= 1 ? 'var(--yellow)' : 'var(--red)' },
+      { label: 'Calmar Ratio',  val: calmar.toFixed(2),         color: 'var(--teal)' },
+      { label: 'Max Drawdown',  val: dd.toFixed(1) + '%',       color: 'var(--red)' },
+      { label: 'Win Rate',      val: wr.toFixed(1) + '%',       color: 'var(--text)' },
+      { label: 'Total Trades',  val: trades.toLocaleString(),   color: 'var(--text)' },
+      { label: 'Score',         val: score.toFixed(4),          color: 'var(--accent2)' },
+      { label: 'Phase',         val: phase,                     color: 'var(--muted)' },
+    ];
+    safe('rd-metrics', e => {
+      e.innerHTML = metrics.map(m =>
+        `<div class="rd-metric">
+          <div class="rd-metric-label">${escapeHtml(m.label)}</div>
+          <div class="rd-metric-val" style="color:${m.color}">${escapeHtml(String(m.val))}</div>
+        </div>`
+      ).join('');
+    });
+
+    // Parameters
+    const params = d.params || {};
+    const paramEntries = Object.entries(params);
+    safe('rd-params-tbody', e => {
+      if (!paramEntries.length) {
+        e.innerHTML = '<tr><td colspan="2" class="empty-state">No parameters available</td></tr>';
+        return;
+      }
+      e.innerHTML = paramEntries.map(([key, val]) => {
+        const display = typeof val === 'number' ? val.toFixed(val % 1 !== 0 ? 4 : 0) : val;
+        return `<tr><td class="param-name">${escapeHtml(key)}</td><td class="param-val">${escapeHtml(String(display))}</td></tr>`;
+      }).join('');
+    });
+
+    // AI Reasoning
+    const ai = d.ai_insight;
+    if (ai) {
+      safe('rd-ai-section', e => { e.style.display = ''; });
+      safe('rd-ai-content', e => {
+        let html = '<div class="rd-ai-box">';
+        const analysisText = ai.analysis || ai.diagnosis || ai.headline || '';
+        if (analysisText) {
+          html += '<div class="rd-ai-analysis">' + escapeHtml(analysisText) + '</div>';
+        }
+        const changes = ai.changes || ai.suggestions || [];
+        if (changes.length) {
+          html += '<div class="ai-sub-title" style="margin-bottom:0.4rem;">Suggested Changes</div>';
+          html += '<div class="rd-ai-changes">';
+          changes.forEach(c => {
+            if (typeof c === 'object' && (c.param || c.parameter)) {
+              const p = c.param || c.parameter;
+              const v = c.value !== undefined ? c.value : (c.to !== undefined ? c.to : '?');
+              html += `<div class="rd-ai-change">
+                <span class="rd-ai-change-param">${escapeHtml(p)}</span>
+                <span class="rd-ai-change-arrow">→</span>
+                <span class="rd-ai-change-val">${escapeHtml(String(v))}</span>
+              </div>`;
+            } else if (typeof c === 'string') {
+              html += `<div class="rd-ai-change"><span style="color:var(--text)">${escapeHtml(c)}</span></div>`;
+            }
+          });
+          html += '</div>';
+        }
+        const conf = ai.confidence;
+        if (conf !== undefined) {
+          const confStr = typeof conf === 'number' ? (conf * 100).toFixed(0) + '%' : String(conf);
+          html += `<div style="margin-top:0.65rem;font-size:0.7rem;color:var(--muted)">Confidence: <strong style="color:var(--text)">${escapeHtml(confStr)}</strong></div>`;
+        }
+        const gs = ai.goal_status;
+        if (gs) {
+          const flags = [
+            gs.profit_factor_met ? '✓ PF' : '✗ PF',
+            gs.drawdown_ok       ? '✓ DD' : '✗ DD',
+            gs.calmar_met        ? '✓ Calmar' : '✗ Calmar',
+          ].join('  ·  ');
+          html += `<div style="margin-top:0.4rem;font-size:0.7rem;color:var(--muted)">Targets: ${escapeHtml(flags)}</div>`;
+        }
+        html += '</div>';
+        e.innerHTML = html;
+      });
+    }
+
+    // Footer
+    safe('rd-footer', e => {
+      let btns = '';
+      if (d.set_url) {
+        btns += `<a href="${escapeHtml(d.set_url)}" class="verdict-btn primary" download>⬇ Download .set</a>`;
+      }
+      const reportHref = '/reports/' + encodeURIComponent(d.run_id || run_id) + '/summary.html';
+      btns += `<a href="${reportHref}" class="verdict-btn secondary" target="_blank">📋 View Report</a>`;
+      btns += '<button class="verdict-btn ghost" onclick="closeRunDetail()">Close</button>';
+      e.innerHTML = btns;
+    });
+
+  } catch (err) {
+    safe('rd-meta', e => { e.textContent = 'Error: ' + err.message; });
+  }
+}
+
+function closeRunDetail() {
+  safe('run-detail-overlay', e => { e.style.display = 'none'; });
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   BEST RESULT — shows full params, AI reasoning, AND evolution path
+══════════════════════════════════════════════════════════════════════ */
+
+async function openBestResult() {
+  try {
+    const resp = await fetch('/api/best_result');
+    if (!resp.ok) {
+      // No best yet — open a toast-like state in the run detail modal
+      safe('run-detail-overlay', e => { e.style.display = 'flex'; });
+      safe('rd-run-id',       e => { e.textContent = 'Best Result'; });
+      safe('rd-meta',         e => { e.textContent = 'No best result yet — optimization must complete at least one passing run.'; });
+      safe('rd-metrics',      e => { e.innerHTML = ''; });
+      safe('rd-params-tbody', e => { e.innerHTML = '<tr><td colspan="2" class="empty-state">—</td></tr>'; });
+      safe('rd-ai-section',   e => { e.style.display = 'none'; });
+      safe('rd-footer',       e => { e.innerHTML = '<button class="verdict-btn ghost" onclick="closeRunDetail()">Close</button>'; });
+      return;
+    }
+    const d = await resp.json();
+    // Delegate to the existing openRunDetail, then append evolution path
+    await openRunDetail(d.run_id);
+    // Append evolution path as an extra section inside the modal body
+    const body = document.querySelector('.run-detail-body');
+    if (!body) return;
+    let evoSection = document.getElementById('rd-evolution-section');
+    if (!evoSection) {
+      evoSection = document.createElement('div');
+      evoSection.id = 'rd-evolution-section';
+      body.appendChild(evoSection);
+    }
+    const evo = d.evolution || [];
+    if (!evo.length) {
+      evoSection.innerHTML = '<div class="rd-section-title">Evolution Path</div><div style="font-size:0.76rem;color:var(--muted);padding:0.5rem 0;">No evolution data available for this run.</div>';
+      return;
+    }
+    const items = evo.map((r, i) => {
+      const tag = r.is_best ? '<span style="background:rgba(16,185,129,0.18);color:var(--green);padding:0.08rem 0.4rem;border-radius:4px;font-size:0.58rem;font-weight:700;margin-left:0.4rem">BEST</span>' : '';
+      const phaseLbl = (r.phase || '').replace(/_/g, ' ');
+      const pf = Number(r.profit_factor || 0).toFixed(2);
+      const calmar = Number(r.calmar || 0).toFixed(2);
+      const dd = Number(r.max_drawdown || 0).toFixed(1);
+      const score = Number(r.score || 0).toFixed(3);
+      const changeList = (r.changes || []).slice(0, 3).map(c => {
+        const p = c.param || c.parameter || '?';
+        const v = c.value !== undefined ? c.value : (c.to !== undefined ? c.to : '?');
+        return `${escapeHtml(p)}=${escapeHtml(String(v))}`;
+      }).join(', ');
+      const analysis = r.analysis ? `<div style="font-size:0.68rem;color:#94a3b8;margin-top:0.25rem;line-height:1.45">${escapeHtml(r.analysis).slice(0, 220)}${r.analysis.length > 220 ? '…' : ''}</div>` : '';
+      return `<div style="border-left:2px solid ${r.is_best ? 'var(--green)' : 'rgba(124,109,250,0.4)'};padding:0.5rem 0.65rem;margin-bottom:0.4rem;background:rgba(255,255,255,0.02);border-radius:0 6px 6px 0">
+        <div style="display:flex;align-items:center;gap:0.5rem;font-size:0.72rem">
+          <span style="font-family:'JetBrains Mono',monospace;color:var(--muted)">#${i + 1}</span>
+          <span style="font-family:'JetBrains Mono',monospace;color:var(--accent2)">${escapeHtml(r.run_id)}</span>
+          <span style="color:var(--muted);font-size:0.6rem;text-transform:uppercase;letter-spacing:0.04em">${escapeHtml(phaseLbl)}</span>
+          ${tag}
+          <span style="margin-left:auto;font-size:0.65rem;font-family:'JetBrains Mono',monospace;color:var(--muted)">score ${score}</span>
+        </div>
+        <div style="display:flex;gap:0.6rem;font-size:0.65rem;color:var(--muted);margin-top:0.2rem;font-family:'JetBrains Mono',monospace">
+          <span>PF ${pf}</span><span>Calmar ${calmar}</span><span>DD ${dd}%</span>
+        </div>
+        ${changeList ? `<div style="font-size:0.66rem;color:var(--teal);font-family:'JetBrains Mono',monospace;margin-top:0.25rem">Δ ${escapeHtml(changeList)}</div>` : ''}
+        ${analysis}
+      </div>`;
+    }).join('');
+    evoSection.innerHTML = `
+      <div class="rd-section-title">Evolution Path <span style="font-weight:500;color:var(--muted);letter-spacing:0.02em;text-transform:none;font-size:0.65rem">— ${evo.length} steps to this best result</span></div>
+      <div style="max-height:260px;overflow-y:auto;padding:0.25rem 0;">${items}</div>
+    `;
+  } catch (err) {
+    addLog('Failed to open best result: ' + err.message, 'error');
+  }
+}
+
+/* ══════════════════════════════════════════════════════════════════════
+   INIT
+══════════════════════════════════════════════════════════════════════ */
+
+(function init() {
+  initSparklines();
+  restoreHistory();
+  startPolling();
+  addLog('APEX Dashboard initialized.', 'success');
+})();
diff --git a/ui/templates/dashboard.html b/ui/templates/dashboard.html
index 475cf53..1a6cf01 100644
--- a/ui/templates/dashboard.html
+++ b/ui/templates/dashboard.html
@@ -3,313 +3,2400 @@
 <head>
   <meta charset="UTF-8">
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
-  <title>MT5 Smart Optimizer — Live Dashboard</title>
+  <title>APEX — AI-Powered EA Optimizer</title>
   <link rel="preconnect" href="https://fonts.googleapis.com">
-  <link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800&family=JetBrains+Mono:wght@400;500&display=swap" rel="stylesheet">
-  <link rel="stylesheet" href="/static/css/style.css">
+  <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+  <link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800&family=JetBrains+Mono:wght@400;500;600&display=swap" rel="stylesheet">
   <style>
-    /* ── Progress bar ─────────────────────────────────────── */
-    .progress-wrap {
-      background: var(--card-bg, #0d1117);
-      border: 1px solid var(--border-color, rgba(255,255,255,0.08));
-      border-radius: 14px;
-      padding: 1.25rem 1.5rem;
-      margin-bottom: 1rem;
+    /* ── CSS Variables ──────────────────────────────────────────── */
+    :root {
+      --bg:              #080d1a;
+      --sidebar-bg:      #0a0f1e;
+      --card-bg:         #0f1629;
+      --card-hover:      #131d35;
+      --border:          rgba(255,255,255,0.07);
+      --border-hover:    rgba(255,255,255,0.14);
+      --accent:          #4f46e5;
+      --accent2:         #7c6dfa;
+      --teal:            #00d4aa;
+      --text:            #e2e8f0;
+      --muted:           #64748b;
+      --green:           #10b981;
+      --red:             #ef4444;
+      --yellow:          #f59e0b;
+      --nav-active-bg:   rgba(79,70,229,0.18);
+      --nav-active-border: #4f46e5;
     }
-    .progress-header { display: flex; justify-content: space-between; align-items: center; margin-bottom: 0.75rem; }
-    .progress-phase { font-size: 0.85rem; font-weight: 600; color: #00d4aa; text-transform: uppercase; letter-spacing: 0.08em; }
-    .progress-count { font-size: 0.82rem; color: #64748b; font-family: 'JetBrains Mono', monospace; }
-    .progress-bar-track { height: 6px; background: rgba(255,255,255,0.06); border-radius: 999px; overflow: hidden; }
-    .progress-bar-fill  { height: 100%; background: linear-gradient(90deg, #00d4aa, #7c6dfa); border-radius: 999px; transition: width 0.5s ease; width: 0%; }
-    .progress-budget { margin-top: 0.5rem; font-size: 0.75rem; color: #64748b; }
 
-    /* ── Phase steps ──────────────────────────────────────── */
-    .phase-steps { display: flex; align-items: center; gap: 0; }
-    .phase-step  { display: flex; flex-direction: column; align-items: center; gap: 0.35rem; flex: 1; position: relative; }
-    .phase-dot   { width: 28px; height: 28px; border-radius: 50%; border: 2px solid rgba(255,255,255,0.12); background: #0d1117; display: grid; place-items: center; font-size: 0.75rem; font-weight: 700; color: #64748b; transition: all 0.4s; z-index: 1; }
-    .phase-name  { font-size: 0.7rem; color: #64748b; font-weight: 500; text-align: center; }
-    .phase-line  { flex: 1; height: 2px; background: rgba(255,255,255,0.08); margin-top: -16px; }
-    .phase-step.active  .phase-dot { border-color: #00d4aa; color: #00d4aa; background: rgba(0,212,170,0.1); box-shadow: 0 0 12px rgba(0,212,170,0.3); }
-    .phase-step.active  .phase-name { color: #00d4aa; }
-    .phase-step.done    .phase-dot { border-color: #00d4aa; background: #00d4aa; color: #051a14; }
-    .phase-step.done    .phase-name { color: #e2e8f0; }
+    /* ── Reset ──────────────────────────────────────────────────── */
+    *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }
 
-    /* ── Phase 1 results table ────────────────────────────── */
-    .results-table-wrap { overflow-x: auto; }
-    .results-table { width: 100%; border-collapse: collapse; font-size: 0.82rem; }
-    .results-table th { color: #64748b; font-size: 0.72rem; font-weight: 600; text-transform: uppercase; letter-spacing: 0.07em; padding: 0.5rem 0.75rem; border-bottom: 1px solid rgba(255,255,255,0.07); text-align: right; }
-    .results-table th:first-child { text-align: left; }
-    .results-table td { padding: 0.6rem 0.75rem; border-bottom: 1px solid rgba(255,255,255,0.04); text-align: right; }
-    .results-table td:first-child { text-align: left; font-family: 'JetBrains Mono', monospace; font-size: 0.75rem; }
-    .results-table tr:hover td { background: rgba(255,255,255,0.02); }
-    .results-table .rank-1 td { color: #00d4aa; }
-    .results-table .rank-1 td:first-child { font-weight: 600; }
-    .profit-pos { color: #00d4aa; }
-    .profit-neg { color: #ef4444; }
-    .badge-pass { display: inline-block; padding: 0.1rem 0.5rem; border-radius: 4px; background: rgba(0,212,170,0.15); color: #00d4aa; font-size: 0.7rem; font-weight: 600; }
-    .badge-fail { display: inline-block; padding: 0.1rem 0.5rem; border-radius: 4px; background: rgba(239,68,68,0.12); color: #ef4444; font-size: 0.7rem; }
-
-    /* ── Verdict banner ───────────────────────────────────── */
-    .verdict-banner {
-      border-radius: 16px;
-      padding: 2rem;
-      margin-bottom: 1rem;
-      display: none;
-      animation: fadeUp 0.5s ease both;
+    body {
+      font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif;
+      background: var(--bg);
+      color: var(--text);
+      height: 100vh;
+      overflow: hidden;
+      font-size: 14px;
+      line-height: 1.5;
     }
-    @keyframes fadeUp { from{opacity:0;transform:translateY(16px)} to{opacity:1;transform:translateY(0)} }
-    .verdict-banner.RECOMMENDED { background: linear-gradient(135deg, rgba(0,212,170,0.12), rgba(0,212,170,0.04)); border: 1px solid rgba(0,212,170,0.3); }
-    .verdict-banner.RISKY       { background: linear-gradient(135deg, rgba(245,158,11,0.12), rgba(245,158,11,0.04)); border: 1px solid rgba(245,158,11,0.3); }
-    .verdict-banner.NOT_RELIABLE{ background: linear-gradient(135deg, rgba(239,68,68,0.12), rgba(239,68,68,0.04)); border: 1px solid rgba(239,68,68,0.3); }
-    .verdict-header { display: flex; align-items: center; gap: 1rem; margin-bottom: 1.25rem; }
-    .verdict-icon { font-size: 2.5rem; }
-    .verdict-title { font-size: 1.6rem; font-weight: 800; letter-spacing: -0.03em; }
-    .verdict-sub   { font-size: 0.85rem; color: #94a3b8; margin-top: 0.2rem; }
-    .verdict-RECOMMENDED .verdict-title { color: #00d4aa; }
-    .verdict-RISKY        .verdict-title { color: #f59e0b; }
-    .verdict-NOT_RELIABLE .verdict-title { color: #ef4444; }
-    .verdict-metrics { display: grid; grid-template-columns: repeat(4, 1fr); gap: 0.75rem; margin-bottom: 1.5rem; }
-    .verdict-metric { background: rgba(255,255,255,0.04); border-radius: 10px; padding: 0.75rem; text-align: center; }
-    .verdict-metric-val { font-size: 1.3rem; font-weight: 700; }
-    .verdict-metric-lbl { font-size: 0.7rem; color: #64748b; text-transform: uppercase; letter-spacing: 0.07em; margin-top: 0.2rem; }
-    .verdict-actions { display: flex; gap: 0.75rem; flex-wrap: wrap; }
-    .btn-download {
-      display: inline-flex; align-items: center; gap: 0.5rem;
-      padding: 0.8rem 1.75rem; border-radius: 10px;
-      background: linear-gradient(135deg, #00d4aa, #00b890);
-      color: #051a14; font-weight: 700; font-family: inherit;
-      font-size: 0.95rem; cursor: pointer; border: none;
+
+    /* ── App shell ──────────────────────────────────────────────── */
+    .app-shell {
+      display: flex;
+      height: 100vh;
+    }
+
+    /* ══════════════════════════════════════════════════════════════
+       SIDEBAR
+    ══════════════════════════════════════════════════════════════ */
+    .sidebar {
+      width: 220px;
+      flex-shrink: 0;
+      background: var(--sidebar-bg);
+      border-right: 1px solid var(--border);
+      display: flex;
+      flex-direction: column;
+      padding: 1.25rem 0;
+      overflow: hidden;
+    }
+
+    /* Logo */
+    .logo-wrap {
+      display: flex;
+      align-items: center;
+      gap: 0.65rem;
+      padding: 0 1.25rem 1.25rem;
+      border-bottom: 1px solid var(--border);
+      margin-bottom: 0.75rem;
+    }
+    .logo-text {
+      font-size: 1.25rem;
+      font-weight: 800;
+      letter-spacing: 0.12em;
+      background: linear-gradient(135deg, #7c6dfa, #00d4aa);
+      -webkit-background-clip: text;
+      -webkit-text-fill-color: transparent;
+      background-clip: text;
+    }
+    .logo-tagline {
+      font-size: 0.58rem;
+      color: var(--muted);
+      font-weight: 400;
+      letter-spacing: 0.06em;
+      display: block;
+      line-height: 1;
+      margin-top: -2px;
+      -webkit-text-fill-color: var(--muted);
+    }
+
+    /* Nav */
+    .sidebar-nav {
+      flex: 1;
+      display: flex;
+      flex-direction: column;
+      gap: 1px;
+      padding: 0.25rem 0;
+    }
+    .nav-section-label {
+      font-size: 0.6rem;
+      font-weight: 700;
+      letter-spacing: 0.1em;
+      text-transform: uppercase;
+      color: var(--muted);
+      padding: 0.75rem 1.25rem 0.35rem;
+    }
+    .nav-item {
+      display: flex;
+      align-items: center;
+      gap: 0.7rem;
+      padding: 0.6rem 1.25rem;
+      color: var(--muted);
       text-decoration: none;
-      box-shadow: 0 4px 20px rgba(0,212,170,0.3);
-      transition: all 0.2s;
+      font-size: 0.83rem;
+      font-weight: 500;
+      transition: all 0.15s ease;
+      border-left: 2px solid transparent;
+      position: relative;
     }
-    .btn-download:hover { transform: translateY(-2px); box-shadow: 0 8px 30px rgba(0,212,170,0.4); }
-    .btn-new-run {
-      display: inline-flex; align-items: center; gap: 0.5rem;
-      padding: 0.8rem 1.5rem; border-radius: 10px;
-      background: rgba(255,255,255,0.06); border: 1px solid rgba(255,255,255,0.1);
-      color: #e2e8f0; font-weight: 600; font-family: inherit;
-      font-size: 0.9rem; cursor: pointer; text-decoration: none;
-      transition: all 0.2s;
+    .nav-item svg { flex-shrink: 0; }
+    .nav-item:hover {
+      color: var(--text);
+      background: rgba(255,255,255,0.04);
+    }
+    .nav-item.active {
+      color: var(--text);
+      background: var(--nav-active-bg);
+      border-left-color: var(--accent);
+    }
+    .nav-item.active svg { color: var(--accent2); }
+    .nav-badge {
+      margin-left: auto;
+      background: var(--accent);
+      color: white;
+      font-size: 0.6rem;
+      font-weight: 700;
+      padding: 0.1rem 0.4rem;
+      border-radius: 999px;
+      min-width: 18px;
+      text-align: center;
     }
-    .btn-new-run:hover { background: rgba(255,255,255,0.1); }
 
-    /* ── No-profit warning ────────────────────────────────── */
-    .no-profit-banner {
-      background: rgba(239,68,68,0.08);
-      border: 1px solid rgba(239,68,68,0.2);
+    /* Sidebar footer */
+    .sidebar-footer {
+      padding: 1rem 1.25rem 0;
+      border-top: 1px solid var(--border);
+      display: flex;
+      flex-direction: column;
+      gap: 0.75rem;
+    }
+    .mt5-status {
+      display: flex;
+      align-items: center;
+      gap: 0.6rem;
+    }
+    .mt5-dot {
+      width: 8px;
+      height: 8px;
+      border-radius: 50%;
+      background: var(--green);
+      box-shadow: 0 0 8px var(--green);
+      animation: pulse-dot 2s ease-in-out infinite;
+      flex-shrink: 0;
+    }
+    .mt5-dot.disconnected {
+      background: var(--red);
+      box-shadow: 0 0 8px var(--red);
+      animation: none;
+    }
+    @keyframes pulse-dot {
+      0%, 100% { opacity: 1; box-shadow: 0 0 8px var(--green); }
+      50% { opacity: 0.6; box-shadow: 0 0 4px var(--green); }
+    }
+    .mt5-label { font-size: 0.68rem; color: var(--muted); font-weight: 500; }
+    .mt5-state  { font-size: 0.75rem; color: var(--text); font-weight: 600; }
+    .mt5-brand  {
+      display: flex;
+      align-items: center;
+      gap: 0.5rem;
+      font-size: 0.7rem;
+      color: var(--muted);
+    }
+
+    /* ══════════════════════════════════════════════════════════════
+       MAIN CONTENT
+    ══════════════════════════════════════════════════════════════ */
+    .main-content {
+      flex: 1;
+      overflow-y: auto;
+      overflow-x: hidden;
+      padding: 1.25rem 1.5rem 1.5rem;
+      display: flex;
+      flex-direction: column;
+      gap: 0.85rem;
+      scrollbar-width: thin;
+      scrollbar-color: rgba(255,255,255,0.1) transparent;
+    }
+    .main-content::-webkit-scrollbar { width: 5px; }
+    .main-content::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.08); border-radius: 999px; }
+
+    /* ── Command Header ──────────────────────────────────────── */
+    .cmd-header {
+      display: flex;
+      align-items: center;
+      background: var(--card-bg);
+      border: 1px solid rgba(79,70,229,0.28);
       border-radius: 14px;
-      padding: 1.5rem;
-      display: none;
-      margin-bottom: 1rem;
+      padding: 0.7rem 1.25rem;
+      flex-shrink: 0;
+      position: relative;
+      overflow: hidden;
+      gap: 0;
     }
-    .no-profit-banner h3 { color: #ef4444; margin-bottom: 0.5rem; }
-    .no-profit-banner p  { color: #94a3b8; font-size: 0.875rem; line-height: 1.6; }
+    .cmd-header::before {
+      content: '';
+      position: absolute;
+      top: 0; left: 0; right: 0; height: 1px;
+      background: linear-gradient(90deg, rgba(0,229,255,0.45), rgba(79,70,229,0.55), rgba(124,58,237,0.45));
+    }
+    .cmd-logo {
+      display: flex;
+      align-items: center;
+      gap: 0.6rem;
+      flex-shrink: 0;
+    }
+    .cmd-logo-text {
+      display: flex;
+      flex-direction: column;
+      gap: 0.05rem;
+    }
+    .cmd-apex {
+      font-size: 1.05rem;
+      font-weight: 800;
+      letter-spacing: 0.14em;
+      background: linear-gradient(135deg, #00e5ff 0%, #4f46e5 50%, #7c3aed 100%);
+      -webkit-background-clip: text;
+      -webkit-text-fill-color: transparent;
+      background-clip: text;
+    }
+    .cmd-tagline {
+      font-size: 0.46rem;
+      font-weight: 600;
+      letter-spacing: 0.1em;
+      color: var(--muted);
+      text-transform: uppercase;
+      -webkit-text-fill-color: var(--muted);
+    }
+    .cmd-sep {
+      width: 1px;
+      height: 30px;
+      background: var(--border);
+      margin: 0 1.1rem;
+      flex-shrink: 0;
+    }
+    .cmd-section {
+      display: flex;
+      flex-direction: column;
+      gap: 0.12rem;
+    }
+    .cmd-gen-section { min-width: 145px; }
+    .cmd-status-row { display: flex; align-items: center; gap: 0.4rem; }
+    .cmd-status-dot {
+      width: 8px; height: 8px;
+      border-radius: 50%;
+      background: var(--muted);
+      flex-shrink: 0;
+      transition: background 0.3s, box-shadow 0.3s;
+    }
+    .cmd-status-dot.running {
+      background: var(--green);
+      box-shadow: 0 0 8px rgba(16,185,129,0.6);
+      animation: pulse-dot 1.5s ease-in-out infinite;
+    }
+    .cmd-status-label {
+      font-size: 0.82rem;
+      font-weight: 600;
+      color: var(--text);
+      white-space: nowrap;
+    }
+    .cmd-section-sub { font-size: 0.66rem; color: var(--muted); white-space: nowrap; }
+    .cmd-gen-row {
+      display: flex;
+      align-items: center;
+      justify-content: space-between;
+      gap: 0.5rem;
+    }
+    .cmd-gen-label {
+      font-size: 0.61rem;
+      font-weight: 700;
+      color: var(--muted);
+      text-transform: uppercase;
+      letter-spacing: 0.07em;
+    }
+    .cmd-gen-val {
+      font-size: 0.8rem;
+      font-weight: 700;
+      color: var(--text);
+      font-family: 'JetBrains Mono', monospace;
+    }
+    .cmd-gen-sep { color: var(--muted); margin: 0 0.1rem; font-weight: 400; }
+    .cmd-prog-track {
+      width: 100%;
+      height: 3px;
+      background: rgba(255,255,255,0.07);
+      border-radius: 999px;
+      overflow: hidden;
+      margin: 0.12rem 0;
+    }
+    .cmd-prog-fill {
+      height: 100%;
+      background: linear-gradient(90deg, #00e5ff, #4f46e5);
+      border-radius: 999px;
+      transition: width 0.5s ease;
+    }
+    .cmd-pct-label { font-size: 0.61rem; color: var(--muted); }
+    .cmd-score-label {
+      font-size: 0.61rem;
+      font-weight: 700;
+      color: var(--muted);
+      text-transform: uppercase;
+      letter-spacing: 0.07em;
+    }
+    .cmd-score-val {
+      font-size: 0.98rem;
+      font-weight: 700;
+      color: var(--teal);
+      font-family: 'JetBrains Mono', monospace;
+    }
+    .cmd-score-delta { font-size: 0.62rem; color: var(--muted); }
+    .cmd-spacer { flex: 1; }
+    .cmd-actions { display: flex; align-items: center; gap: 0.45rem; flex-shrink: 0; }
+    .cmd-btn {
+      display: inline-flex;
+      align-items: center;
+      gap: 0.35rem;
+      padding: 0.45rem 0.85rem;
+      border-radius: 8px;
+      font-size: 0.76rem;
+      font-weight: 600;
+      cursor: pointer;
+      border: 1px solid transparent;
+      font-family: inherit;
+      transition: all 0.15s;
+      text-decoration: none;
+      white-space: nowrap;
+    }
+    .cmd-btn-start {
+      background: linear-gradient(135deg, #4f46e5, #7c6dfa);
+      color: white;
+    }
+    .cmd-btn-start:hover { opacity: 0.88; }
+    .cmd-btn-pause {
+      background: rgba(245,158,11,0.1);
+      border-color: rgba(245,158,11,0.25);
+      color: var(--yellow);
+      opacity: 0.4;
+      pointer-events: none;
+    }
+    .cmd-btn-pause.active { opacity: 1; pointer-events: auto; }
+    .cmd-btn-pause.active:hover { background: rgba(245,158,11,0.18); }
+    .cmd-btn-stop {
+      background: rgba(100,116,139,0.08);
+      border-color: rgba(100,116,139,0.2);
+      color: var(--muted);
+      opacity: 0.4;
+      pointer-events: none;
+    }
+    .cmd-btn-stop.active {
+      background: rgba(239,68,68,0.12);
+      border-color: rgba(239,68,68,0.35);
+      color: var(--red);
+      opacity: 1;
+      pointer-events: auto;
+    }
+    .cmd-btn-stop.active:hover { background: rgba(239,68,68,0.22); }
+    /* keep run-indicator wiring for JS compat, always hidden */
+    #run-indicator { display: none !important; }
 
-    /* ── Updated candidate card ───────────────────────────── */
-    .cand-card { background: rgba(255,255,255,0.03); border: 1px solid rgba(255,255,255,0.07); border-radius: 12px; padding: 1rem; margin-bottom: 0.75rem; }
-    .cand-header { display: flex; justify-content: space-between; align-items: center; margin-bottom: 0.5rem; }
-    .cand-rank   { font-size: 0.75rem; font-weight: 700; color: #00d4aa; }
-    .cand-run-id { font-family: 'JetBrains Mono', monospace; font-size: 0.72rem; color: #64748b; }
-    .cand-score-row { display: flex; gap: 1.5rem; font-size: 0.82rem; flex-wrap: wrap; }
-    .cand-metric { display: flex; flex-direction: column; gap: 0.1rem; }
-    .cand-metric-lbl { font-size: 0.68rem; color: #64748b; text-transform: uppercase; letter-spacing: 0.06em; }
-    .cand-metric-val { font-weight: 600; }
+    /* ── Metric cards row ────────────────────────────────────── */
+    .metrics-row {
+      display: grid;
+      grid-template-columns: repeat(6, minmax(0, 1fr));
+      gap: 0.7rem;
+      flex-shrink: 0;
+    }
+    .metric-card {
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 12px;
+      padding: 0.9rem 1rem;
+      transition: border-color 0.2s, transform 0.15s;
+      position: relative;
+      overflow: hidden;
+    }
+    .metric-card::before {
+      content: '';
+      position: absolute;
+      top: 0; left: 0; right: 0;
+      height: 2px;
+      background: linear-gradient(90deg, var(--accent), var(--accent2));
+      opacity: 0;
+      transition: opacity 0.2s;
+    }
+    .metric-card:hover { border-color: var(--border-hover); }
+    .metric-card:hover::before { opacity: 1; }
+    .metric-label  { font-size: 0.68rem; color: var(--muted); font-weight: 600; letter-spacing: 0.04em; text-transform: uppercase; margin-bottom: 0.3rem; }
+    .metric-value  { font-size: 1.35rem; font-weight: 700; letter-spacing: -0.02em; line-height: 1.1; }
+    .metric-value.green  { color: var(--green); }
+    .metric-value.red    { color: var(--red); }
+    .metric-value.gold   { color: var(--yellow); }
+    .metric-value.teal   { color: var(--teal); }
+    .metric-value.white  { color: var(--text); }
+    .metric-delta {
+      font-size: 0.7rem;
+      color: var(--muted);
+      margin-top: 0.2rem;
+      display: flex;
+      align-items: center;
+      gap: 0.2rem;
+    }
+    .delta-up   { color: var(--green); }
+    .delta-down { color: var(--red); }
+    .sparkline-wrap {
+      margin-top: 0.55rem;
+    }
+
+    /* AI Confidence card */
+    .ai-conf-card { display: flex; flex-direction: column; }
+    .ai-conf-value {
+      font-size: 0.95rem;
+      font-weight: 700;
+      color: var(--text);
+      margin-top: 0.15rem;
+    }
+    .ai-gauge-wrap {
+      margin-top: 0.45rem;
+      display: flex;
+      align-items: center;
+      justify-content: flex-start;
+    }
+
+    /* ── Charts + AI panel row ───────────────────────────────── */
+    .charts-ai-row {
+      display: grid;
+      grid-template-columns: 2fr 1fr;
+      gap: 0.7rem;
+      flex-shrink: 0;
+    }
+    .charts-col {
+      display: flex;
+      flex-direction: column;
+      gap: 0.7rem;
+    }
+
+    /* Card base */
+    .card {
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 12px;
+      padding: 1rem 1.25rem;
+      display: flex;
+      flex-direction: column;
+    }
+    .card-header {
+      display: flex;
+      align-items: center;
+      justify-content: space-between;
+      margin-bottom: 0.6rem;
+      flex-shrink: 0;
+    }
+    .card-title {
+      font-size: 0.82rem;
+      font-weight: 600;
+      color: var(--text);
+      display: flex;
+      align-items: center;
+      gap: 0.5rem;
+    }
+    .card-title .dot {
+      width: 7px; height: 7px; border-radius: 50%;
+      background: var(--teal);
+    }
+    .card-badge {
+      font-size: 0.65rem;
+      font-weight: 600;
+      padding: 0.15rem 0.5rem;
+      border-radius: 999px;
+      background: rgba(0,212,170,0.12);
+      color: var(--teal);
+    }
+    .chart-wrap {
+      position: relative;
+      overflow: hidden;
+    }
+    .chart-wrap canvas {
+      position: absolute !important;
+      inset: 0;
+      width: 100% !important;
+      height: 100% !important;
+    }
+    .equity-chart-wrap   { height: 165px; }
+    .drawdown-chart-wrap { height: 100px; }
+
+    /* ── AI Summary panel ────────────────────────────────────── */
+    .ai-panel-col {
+      display: flex;
+      flex-direction: column;
+    }
+    .ai-panel-card {
+      background: var(--card-bg);
+      border: 1px solid rgba(79,70,229,0.3);
+      border-radius: 12px;
+      padding: 1rem 1.25rem;
+      flex: 1;
+      display: flex;
+      flex-direction: column;
+      gap: 0.75rem;
+      position: relative;
+      overflow: hidden;
+    }
+    .ai-panel-card::before {
+      content: '';
+      position: absolute;
+      top: 0; left: 0; right: 0; height: 1px;
+      background: linear-gradient(90deg, transparent, rgba(124,109,250,0.6), transparent);
+    }
+    .ai-panel-card::after {
+      content: '';
+      position: absolute;
+      top: -80px; right: -80px;
+      width: 200px; height: 200px;
+      background: radial-gradient(circle, rgba(79,70,229,0.06) 0%, transparent 70%);
+      pointer-events: none;
+    }
+    .ai-panel-header {
+      display: flex;
+      justify-content: space-between;
+      align-items: center;
+      flex-shrink: 0;
+    }
+    .ai-panel-title {
+      font-size: 0.82rem;
+      font-weight: 600;
+      display: flex;
+      align-items: center;
+      gap: 0.4rem;
+    }
+    .ai-icon {
+      color: var(--accent2);
+      font-size: 0.9rem;
+    }
+    .view-details-link {
+      font-size: 0.72rem;
+      color: var(--accent2);
+      text-decoration: none;
+      transition: opacity 0.15s;
+    }
+    .view-details-link:hover { opacity: 0.7; }
+    .ai-waiting {
+      display: flex;
+      flex-direction: column;
+      align-items: center;
+      justify-content: center;
+      flex: 1;
+      gap: 0.75rem;
+      color: var(--muted);
+      font-size: 0.78rem;
+    }
+    .ai-pulse-dot {
+      width: 32px; height: 32px;
+      border-radius: 50%;
+      border: 2px solid rgba(124,109,250,0.4);
+      position: relative;
+      animation: ai-spin 2s linear infinite;
+    }
+    .ai-pulse-dot::before {
+      content: '';
+      position: absolute;
+      top: 4px; left: 4px; right: 4px; bottom: 4px;
+      border-radius: 50%;
+      background: rgba(124,109,250,0.3);
+      animation: ai-pulse 2s ease-in-out infinite;
+    }
+    @keyframes ai-spin { from { transform: rotate(0deg); } to { transform: rotate(360deg); } }
+    @keyframes ai-pulse { 0%,100% { opacity: 0.4; } 50% { opacity: 1; } }
+
+    .ai-content { display: flex; flex-direction: column; gap: 0.65rem; overflow-y: auto; flex: 1; }
+    .ai-content::-webkit-scrollbar { width: 3px; }
+    .ai-content::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.08); border-radius: 999px; }
+    .ai-headline {
+      font-size: 0.82rem;
+      font-weight: 600;
+      color: var(--text);
+      line-height: 1.4;
+      padding-bottom: 0.5rem;
+      border-bottom: 1px solid var(--border);
+    }
+    .ai-diagnosis { font-size: 0.78rem; line-height: 1.7; color: #94a3b8; }
+    .ai-sub-title {
+      font-size: 0.65rem;
+      font-weight: 700;
+      text-transform: uppercase;
+      letter-spacing: 0.09em;
+      color: var(--muted);
+      margin-bottom: 0.35rem;
+    }
+    .ai-sub-title.warn { color: #f59e0b; }
+    .ai-check-list { list-style: none; display: flex; flex-direction: column; gap: 0.3rem; }
+    .ai-check-list li {
+      font-size: 0.76rem;
+      color: var(--text);
+      display: flex;
+      align-items: flex-start;
+      gap: 0.45rem;
+      line-height: 1.4;
+    }
+    .ai-check-list li::before { content: "✓"; color: var(--green); font-weight: 700; flex-shrink: 0; margin-top: 0.05em; }
+    .ai-warn-list { list-style: none; display: flex; flex-direction: column; gap: 0.3rem; }
+    .ai-warn-list li {
+      font-size: 0.76rem;
+      color: #fbbf24;
+      display: flex;
+      align-items: flex-start;
+      gap: 0.45rem;
+      line-height: 1.4;
+    }
+    .ai-warn-list li::before { content: "⚠"; flex-shrink: 0; margin-top: 0.05em; font-size: 0.7rem; }
+    .ai-suggestion-box {
+      background: rgba(79,70,229,0.1);
+      border: 1px solid rgba(79,70,229,0.22);
+      border-radius: 8px;
+      padding: 0.7rem 0.75rem;
+      position: relative;
+    }
+    .ai-suggestion-text { font-size: 0.76rem; color: var(--text); line-height: 1.55; padding-right: 1.5rem; }
+    .ai-badge {
+      position: absolute;
+      top: 0.45rem;
+      right: 0.45rem;
+      background: var(--accent);
+      color: white;
+      font-size: 0.58rem;
+      font-weight: 700;
+      padding: 0.1rem 0.35rem;
+      border-radius: 4px;
+      letter-spacing: 0.04em;
+    }
+    .ai-confidence-row {
+      display: flex;
+      align-items: center;
+      gap: 0.6rem;
+      margin-top: auto;
+      padding-top: 0.5rem;
+      border-top: 1px solid var(--border);
+      flex-shrink: 0;
+    }
+    .ai-conf-badge {
+      display: inline-flex;
+      align-items: center;
+      gap: 0.3rem;
+      padding: 0.2rem 0.6rem;
+      border-radius: 6px;
+      font-size: 0.7rem;
+      font-weight: 600;
+      text-transform: capitalize;
+    }
+    .ai-conf-badge::before { content: '●'; font-size: 0.5rem; }
+    .ai-conf-badge.high   { background: rgba(16,185,129,0.15); color: #10b981; }
+    .ai-conf-badge.medium { background: rgba(245,158,11,0.15);  color: #f59e0b; }
+    .ai-conf-badge.low    { background: rgba(239,68,68,0.15);   color: #ef4444; }
+    .ai-run-ref { font-size: 0.68rem; color: var(--muted); margin-left: auto; font-family: 'JetBrains Mono', monospace; }
+
+    /* ── Bottom row ──────────────────────────────────────────── */
+    .bottom-row {
+      display: grid;
+      grid-template-columns: repeat(3, minmax(0, 1fr));
+      gap: 0.7rem;
+      flex-shrink: 0;
+    }
+    .bottom-card {
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 12px;
+      padding: 0.9rem 1rem;
+      display: flex;
+      flex-direction: column;
+    }
+    .bottom-card-title {
+      font-size: 0.8rem;
+      font-weight: 600;
+      margin-bottom: 0.6rem;
+      display: flex;
+      justify-content: space-between;
+      align-items: center;
+      flex-shrink: 0;
+    }
+    .view-all-link {
+      font-size: 0.7rem;
+      color: var(--accent2);
+      text-decoration: none;
+      font-weight: 500;
+    }
+    .view-all-link:hover { opacity: 0.75; }
+
+    /* Tables */
+    .params-table, .runs-table {
+      width: 100%;
+      border-collapse: collapse;
+      font-size: 0.76rem;
+    }
+    .params-table th, .runs-table th {
+      color: var(--muted);
+      font-size: 0.64rem;
+      font-weight: 700;
+      text-transform: uppercase;
+      letter-spacing: 0.07em;
+      padding: 0.3rem 0.5rem;
+      border-bottom: 1px solid var(--border);
+      text-align: left;
+    }
+    .params-table td, .runs-table td {
+      padding: 0.38rem 0.5rem;
+      border-bottom: 1px solid rgba(255,255,255,0.03);
+      vertical-align: middle;
+    }
+    .params-table tr:last-child td, .runs-table tr:last-child td { border-bottom: none; }
+    .params-table tr:hover td, .runs-table tr:hover td { background: rgba(255,255,255,0.02); }
+    .param-name { font-family: 'JetBrains Mono', monospace; font-size: 0.7rem; color: var(--text); }
+    .param-val  { font-family: 'JetBrains Mono', monospace; font-size: 0.72rem; color: var(--teal); font-weight: 600; }
+    .impact-high   { display: inline-block; background: rgba(16,185,129,0.15); color: var(--green); padding: 0.08rem 0.4rem; border-radius: 4px; font-size: 0.64rem; font-weight: 700; }
+    .impact-medium { display: inline-block; background: rgba(245,158,11,0.15);  color: var(--yellow); padding: 0.08rem 0.4rem; border-radius: 4px; font-size: 0.64rem; font-weight: 700; }
+    .impact-low    { display: inline-block; background: rgba(100,116,139,0.15); color: var(--muted);  padding: 0.08rem 0.4rem; border-radius: 4px; font-size: 0.64rem; font-weight: 700; }
+    .verdict-recommended  { display: inline-block; background: rgba(16,185,129,0.15); color: var(--green);  padding: 0.08rem 0.45rem; border-radius: 4px; font-size: 0.64rem; font-weight: 700; }
+    .verdict-risky        { display: inline-block; background: rgba(245,158,11,0.15);  color: var(--yellow); padding: 0.08rem 0.45rem; border-radius: 4px; font-size: 0.64rem; font-weight: 700; }
+    .verdict-not-reliable { display: inline-block; background: rgba(239,68,68,0.15);   color: var(--red);    padding: 0.08rem 0.45rem; border-radius: 4px; font-size: 0.64rem; font-weight: 700; }
+    .empty-state { color: var(--muted); font-size: 0.76rem; padding: 0.65rem 0.5rem; }
+    .run-num { font-family: 'JetBrains Mono', monospace; font-size: 0.7rem; color: var(--muted); }
+    .profit-pos { color: var(--green); font-weight: 600; }
+    .profit-neg { color: var(--red);   font-weight: 600; }
+
+    /* Optimization progress */
+    .opt-gen-label {
+      font-size: 0.75rem;
+      color: var(--muted);
+      font-family: 'JetBrains Mono', monospace;
+      margin-bottom: 0.45rem;
+    }
+    .opt-progress-bar-track {
+      height: 5px;
+      background: rgba(255,255,255,0.06);
+      border-radius: 999px;
+      overflow: hidden;
+      margin-bottom: 0.65rem;
+    }
+    .opt-progress-bar-fill {
+      height: 100%;
+      background: linear-gradient(90deg, var(--accent), var(--teal));
+      border-radius: 999px;
+      transition: width 0.6s ease;
+      width: 0%;
+    }
+    .opt-stats-grid {
+      display: grid;
+      grid-template-columns: 1fr 1fr 1fr;
+      gap: 0.5rem;
+    }
+    .opt-stat { }
+    .opt-stat-label { font-size: 0.63rem; color: var(--muted); font-weight: 600; text-transform: uppercase; letter-spacing: 0.06em; }
+    .opt-stat-val   { font-size: 0.8rem; color: var(--text); font-weight: 600; margin-top: 0.15rem; }
+
+    /* Phase steps */
+    .phase-steps {
+      display: flex;
+      align-items: center;
+      margin-top: 0.6rem;
+      gap: 0;
+    }
+    .phase-step {
+      display: flex;
+      flex-direction: column;
+      align-items: center;
+      gap: 0.3rem;
+      flex: 1;
+      position: relative;
+    }
+    .phase-dot {
+      width: 24px; height: 24px;
+      border-radius: 50%;
+      border: 2px solid rgba(255,255,255,0.1);
+      background: var(--bg);
+      display: flex; align-items: center; justify-content: center;
+      font-size: 0.65rem;
+      font-weight: 700;
+      color: var(--muted);
+      transition: all 0.35s;
+      z-index: 1;
+    }
+    .phase-name { font-size: 0.6rem; color: var(--muted); font-weight: 500; text-align: center; }
+    .phase-connector {
+      flex: 1;
+      height: 2px;
+      background: rgba(255,255,255,0.07);
+      margin-top: -14px;
+    }
+    .phase-step.active .phase-dot { border-color: var(--teal); color: var(--teal); background: rgba(0,212,170,0.1); box-shadow: 0 0 10px rgba(0,212,170,0.25); }
+    .phase-step.active .phase-name { color: var(--teal); }
+    .phase-step.done   .phase-dot { border-color: var(--teal); background: var(--teal); color: #051a14; }
+    .phase-step.done   .phase-name { color: var(--text); }
+
+    /* ── Live log ────────────────────────────────────────────── */
+    .log-panel {
+      flex-shrink: 0;
+    }
+    .log-toggle-btn {
+      width: 100%;
+      display: flex;
+      align-items: center;
+      justify-content: space-between;
+      padding: 0.5rem 1rem;
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 8px;
+      cursor: pointer;
+      font-family: inherit;
+      font-size: 0.75rem;
+      color: var(--muted);
+      font-weight: 500;
+      transition: all 0.15s;
+    }
+    .log-toggle-btn:hover { color: var(--text); border-color: var(--border-hover); }
+    .log-toggle-icon { transition: transform 0.2s; }
+    .log-toggle-icon.open { transform: rotate(180deg); }
+    .log-body {
+      display: none;
+      margin-top: 0.35rem;
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 8px;
+      overflow: hidden;
+    }
+    .log-body.open { display: block; }
+    .log-feed {
+      height: 120px;
+      overflow-y: auto;
+      padding: 0.6rem 0.75rem;
+      font-family: 'JetBrains Mono', monospace;
+      font-size: 0.7rem;
+      line-height: 1.7;
+      color: #64748b;
+      scrollbar-width: thin;
+      scrollbar-color: rgba(255,255,255,0.06) transparent;
+    }
+    .log-feed::-webkit-scrollbar { width: 3px; }
+    .log-line { display: flex; gap: 0.6rem; }
+    .log-time { color: rgba(100,116,139,0.6); flex-shrink: 0; }
+    .log-line.info   .log-msg { color: #94a3b8; }
+    .log-line.success .log-msg { color: var(--green); }
+    .log-line.warn   .log-msg { color: var(--yellow); }
+    .log-line.error  .log-msg { color: var(--red); }
+
+    /* ── Verdict overlay ─────────────────────────────────────── */
+    .verdict-overlay {
+      position: fixed; inset: 0;
+      background: rgba(0,0,0,0.75);
+      display: flex;
+      align-items: center;
+      justify-content: center;
+      z-index: 200;
+      backdrop-filter: blur(5px);
+    }
+    .verdict-card {
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 20px;
+      padding: 2.25rem 2.5rem;
+      max-width: 580px;
+      width: 92%;
+      animation: popIn 0.4s cubic-bezier(0.34,1.56,0.64,1) both;
+    }
+    @keyframes popIn {
+      from { opacity: 0; transform: scale(0.88) translateY(20px); }
+      to   { opacity: 1; transform: scale(1) translateY(0); }
+    }
+    .verdict-header-row {
+      display: flex;
+      align-items: center;
+      gap: 1.25rem;
+      margin-bottom: 1.5rem;
+    }
+    .verdict-icon-big { font-size: 2.5rem; line-height: 1; }
+    .verdict-title {
+      font-size: 1.5rem;
+      font-weight: 800;
+      letter-spacing: -0.02em;
+    }
+    .verdict-subtitle { font-size: 0.85rem; color: var(--muted); margin-top: 0.25rem; line-height: 1.5; }
+    .verdict-metrics-row {
+      display: grid;
+      grid-template-columns: repeat(4, 1fr);
+      gap: 1rem;
+      padding: 1.25rem 0;
+      border-top: 1px solid var(--border);
+      border-bottom: 1px solid var(--border);
+      margin-bottom: 1.5rem;
+    }
+    .vm { text-align: center; }
+    .vm-val { font-size: 1.1rem; font-weight: 700; }
+    .vm-lbl { font-size: 0.68rem; color: var(--muted); margin-top: 0.2rem; font-weight: 500; }
+    .verdict-actions-row {
+      display: flex;
+      gap: 0.65rem;
+      flex-wrap: wrap;
+    }
+    .verdict-btn {
+      display: inline-flex;
+      align-items: center;
+      gap: 0.4rem;
+      padding: 0.6rem 1.1rem;
+      border-radius: 8px;
+      font-size: 0.82rem;
+      font-weight: 600;
+      cursor: pointer;
+      text-decoration: none;
+      font-family: inherit;
+      border: 1px solid transparent;
+      transition: all 0.15s;
+    }
+    .verdict-btn.primary { background: linear-gradient(135deg, var(--accent), var(--accent2)); color: white; }
+    .verdict-btn.primary:hover { opacity: 0.88; }
+    .verdict-btn.secondary { background: rgba(255,255,255,0.06); border-color: var(--border); color: var(--text); }
+    .verdict-btn.secondary:hover { background: rgba(255,255,255,0.1); }
+    .verdict-btn.ghost { background: transparent; border-color: rgba(255,255,255,0.1); color: var(--muted); }
+    .verdict-btn.ghost:hover { color: var(--text); }
+
+    /* ── Settings Modal ─────────────────────────────────────── */
+    .settings-overlay {
+      position: fixed; inset: 0;
+      background: rgba(0,0,0,0.78);
+      display: flex;
+      align-items: center;
+      justify-content: center;
+      z-index: 300;
+      backdrop-filter: blur(6px);
+      animation: fadeIn 0.2s ease both;
+    }
+    @keyframes fadeIn { from { opacity: 0; } to { opacity: 1; } }
+    .settings-card {
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 18px;
+      width: 680px;
+      max-width: 95vw;
+      max-height: 90vh;
+      display: flex;
+      flex-direction: column;
+      overflow: hidden;
+      animation: popIn 0.3s cubic-bezier(0.34,1.56,0.64,1) both;
+    }
+    .settings-header {
+      display: flex;
+      align-items: center;
+      justify-content: space-between;
+      padding: 1.25rem 1.5rem;
+      border-bottom: 1px solid var(--border);
+      flex-shrink: 0;
+    }
+    .settings-title {
+      font-size: 1rem;
+      font-weight: 700;
+      letter-spacing: -0.01em;
+      display: flex;
+      align-items: center;
+      gap: 0.6rem;
+    }
+    .settings-title svg { color: var(--accent2); }
+    .settings-close-btn {
+      width: 28px; height: 28px;
+      border-radius: 50%;
+      background: rgba(255,255,255,0.06);
+      border: 1px solid var(--border);
+      color: var(--muted);
+      cursor: pointer;
+      display: flex;
+      align-items: center;
+      justify-content: center;
+      transition: all 0.15s;
+      font-size: 14px;
+      line-height: 1;
+    }
+    .settings-close-btn:hover { background: rgba(255,255,255,0.12); color: var(--text); }
+    .settings-tabs {
+      display: flex;
+      gap: 0;
+      padding: 0 1.5rem;
+      border-bottom: 1px solid var(--border);
+      flex-shrink: 0;
+      overflow-x: auto;
+    }
+    .settings-tab {
+      padding: 0.65rem 1rem;
+      font-size: 0.78rem;
+      font-weight: 600;
+      color: var(--muted);
+      cursor: pointer;
+      border-bottom: 2px solid transparent;
+      transition: all 0.15s;
+      white-space: nowrap;
+      display: flex;
+      align-items: center;
+      gap: 0.4rem;
+    }
+    .settings-tab:hover { color: var(--text); }
+    .settings-tab.active { color: var(--text); border-bottom-color: var(--accent); }
+    .settings-body {
+      flex: 1;
+      overflow-y: auto;
+      padding: 1.5rem;
+      scrollbar-width: thin;
+      scrollbar-color: rgba(255,255,255,0.1) transparent;
+    }
+    .settings-panel { display: none; }
+    .settings-panel.active { display: block; }
+    .settings-section-label {
+      font-size: 0.62rem;
+      font-weight: 700;
+      letter-spacing: 0.1em;
+      text-transform: uppercase;
+      color: var(--muted);
+      margin-bottom: 0.75rem;
+      margin-top: 1.25rem;
+    }
+    .settings-section-label:first-child { margin-top: 0; }
+    .settings-grid {
+      display: grid;
+      grid-template-columns: 1fr 1fr;
+      gap: 0.75rem;
+    }
+    .settings-grid.full { grid-template-columns: 1fr; }
+    .settings-field {
+      display: flex;
+      flex-direction: column;
+      gap: 0.35rem;
+    }
+    .settings-field label {
+      font-size: 0.72rem;
+      font-weight: 600;
+      color: var(--muted);
+      letter-spacing: 0.02em;
+    }
+    .settings-input {
+      background: rgba(255,255,255,0.04);
+      border: 1px solid var(--border);
+      border-radius: 7px;
+      padding: 0.5rem 0.75rem;
+      color: var(--text);
+      font-size: 0.82rem;
+      font-family: inherit;
+      transition: border-color 0.15s;
+      width: 100%;
+    }
+    .settings-input:focus {
+      outline: none;
+      border-color: var(--accent);
+      background: rgba(79,70,229,0.06);
+    }
+    .settings-input.mono { font-family: 'JetBrains Mono', monospace; font-size: 0.78rem; }
+    .settings-select {
+      background: rgba(255,255,255,0.04);
+      border: 1px solid var(--border);
+      border-radius: 7px;
+      padding: 0.5rem 0.75rem;
+      color: var(--text);
+      font-size: 0.82rem;
+      font-family: inherit;
+      transition: border-color 0.15s;
+      width: 100%;
+      cursor: pointer;
+    }
+    .settings-select:focus { outline: none; border-color: var(--accent); }
+    .settings-select option { background: #0f1629; }
+    .settings-toggle-row {
+      display: flex;
+      align-items: center;
+      justify-content: space-between;
+      background: rgba(255,255,255,0.03);
+      border: 1px solid var(--border);
+      border-radius: 8px;
+      padding: 0.6rem 0.85rem;
+    }
+    .settings-toggle-label { font-size: 0.82rem; font-weight: 500; }
+    .settings-toggle-sub { font-size: 0.7rem; color: var(--muted); margin-top: 0.15rem; }
+    .settings-toggle {
+      width: 40px; height: 22px;
+      background: rgba(255,255,255,0.12);
+      border-radius: 999px;
+      border: none;
+      cursor: pointer;
+      position: relative;
+      transition: background 0.2s;
+      flex-shrink: 0;
+    }
+    .settings-toggle::after {
+      content: '';
+      position: absolute;
+      top: 3px; left: 3px;
+      width: 16px; height: 16px;
+      border-radius: 50%;
+      background: white;
+      transition: transform 0.2s;
+    }
+    .settings-toggle.on { background: var(--accent); }
+    .settings-toggle.on::after { transform: translateX(18px); }
+    .settings-hint {
+      font-size: 0.68rem;
+      color: var(--muted);
+      margin-top: 0.2rem;
+      line-height: 1.4;
+    }
+    .settings-footer {
+      display: flex;
+      align-items: center;
+      justify-content: flex-end;
+      gap: 0.65rem;
+      padding: 1rem 1.5rem;
+      border-top: 1px solid var(--border);
+      flex-shrink: 0;
+    }
+    .settings-btn {
+      display: inline-flex;
+      align-items: center;
+      gap: 0.4rem;
+      padding: 0.55rem 1.1rem;
+      border-radius: 8px;
+      font-size: 0.82rem;
+      font-weight: 600;
+      cursor: pointer;
+      font-family: inherit;
+      border: 1px solid transparent;
+      transition: all 0.15s;
+    }
+    .settings-btn.cancel {
+      background: rgba(255,255,255,0.05);
+      border-color: var(--border);
+      color: var(--muted);
+    }
+    .settings-btn.cancel:hover { background: rgba(255,255,255,0.1); color: var(--text); }
+    .settings-btn.save {
+      background: linear-gradient(135deg, var(--accent), var(--accent2));
+      color: white;
+    }
+    .settings-btn.save:hover { opacity: 0.88; }
+    .settings-btn.save:disabled { opacity: 0.5; cursor: not-allowed; }
+    .settings-save-msg {
+      font-size: 0.75rem;
+      font-weight: 600;
+      margin-right: auto;
+      transition: opacity 0.3s;
+    }
+    .settings-save-msg.ok  { color: var(--green); }
+    .settings-save-msg.err { color: var(--red); }
+
+    /* ── No profit state banner ──────────────────────────────── */
+    .no-profit-banner {
+      display: none;
+      align-items: center;
+      gap: 0.75rem;
+      padding: 0.75rem 1rem;
+      background: rgba(239,68,68,0.1);
+      border: 1px solid rgba(239,68,68,0.25);
+      border-radius: 10px;
+      font-size: 0.8rem;
+      color: var(--red);
+    }
+    .no-profit-banner.active { display: flex; }
+    .no-profit-banner-icon { font-size: 1.1rem; flex-shrink: 0; }
+
+    /* ── Scrollbar for whole page ────────────────────────────── */
+    ::-webkit-scrollbar        { width: 5px; height: 5px; }
+    ::-webkit-scrollbar-track  { background: transparent; }
+    ::-webkit-scrollbar-thumb  { background: rgba(255,255,255,0.08); border-radius: 999px; }
+
+    /* ── AI panel expand / collapse ─────────────────────────── */
+    .ai-preview { display: flex; flex-direction: column; gap: 0.5rem; }
+    .ai-details { display: none; flex-direction: column; gap: 0.65rem; }
+    .ai-details.open { display: flex; animation: slideDown 0.2s ease; }
+    @keyframes slideDown { from { opacity:0; transform:translateY(-6px); } to { opacity:1; transform:translateY(0); } }
+    .ai-expand-btn {
+      align-self: flex-start;
+      background: rgba(79,70,229,0.12);
+      border: 1px solid rgba(79,70,229,0.28);
+      border-radius: 6px;
+      color: var(--accent2);
+      font-size: 0.72rem;
+      font-weight: 600;
+      padding: 0.25rem 0.65rem;
+      cursor: pointer;
+      font-family: inherit;
+      transition: all 0.15s;
+      margin-top: 0.15rem;
+    }
+    .ai-expand-btn:hover { background: rgba(79,70,229,0.22); }
+
+    /* ── Details button in runs table ───────────────────────── */
+    .detail-btn {
+      background: rgba(79,70,229,0.1);
+      border: 1px solid rgba(79,70,229,0.22);
+      border-radius: 5px;
+      color: var(--accent2);
+      font-size: 0.65rem;
+      font-weight: 600;
+      padding: 0.15rem 0.5rem;
+      cursor: pointer;
+      font-family: inherit;
+      transition: all 0.15s;
+      white-space: nowrap;
+    }
+    .detail-btn:hover { background: rgba(79,70,229,0.22); }
+
+    /* ── Run Detail Modal ────────────────────────────────────── */
+    .run-detail-overlay {
+      position: fixed; inset: 0;
+      background: rgba(0,0,0,0.78);
+      display: flex;
+      align-items: center;
+      justify-content: center;
+      z-index: 250;
+      backdrop-filter: blur(5px);
+    }
+    .run-detail-card {
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 18px;
+      width: 720px;
+      max-width: 95vw;
+      max-height: 88vh;
+      display: flex;
+      flex-direction: column;
+      overflow: hidden;
+      animation: popIn 0.3s cubic-bezier(0.34,1.56,0.64,1) both;
+    }
+    .run-detail-header {
+      display: flex;
+      align-items: flex-start;
+      justify-content: space-between;
+      padding: 1.1rem 1.5rem;
+      border-bottom: 1px solid var(--border);
+      flex-shrink: 0;
+    }
+    .run-detail-title {
+      font-size: 0.95rem;
+      font-weight: 700;
+      color: var(--text);
+      font-family: 'JetBrains Mono', monospace;
+      letter-spacing: 0.02em;
+    }
+    .run-detail-sub { font-size: 0.72rem; color: var(--muted); margin-top: 0.2rem; }
+    .run-detail-body {
+      flex: 1;
+      overflow-y: auto;
+      padding: 1.1rem 1.5rem;
+      display: flex;
+      flex-direction: column;
+      gap: 1rem;
+      scrollbar-width: thin;
+      scrollbar-color: rgba(255,255,255,0.1) transparent;
+    }
+    .rd-metrics-grid {
+      display: grid;
+      grid-template-columns: repeat(4, 1fr);
+      gap: 0.6rem;
+    }
+    .rd-metric {
+      background: rgba(255,255,255,0.03);
+      border: 1px solid var(--border);
+      border-radius: 9px;
+      padding: 0.65rem 0.8rem;
+    }
+    .rd-metric-label { font-size: 0.6rem; font-weight: 700; color: var(--muted); text-transform: uppercase; letter-spacing: 0.06em; }
+    .rd-metric-val { font-size: 1rem; font-weight: 700; margin-top: 0.15rem; }
+    .rd-section-title {
+      font-size: 0.63rem;
+      font-weight: 700;
+      text-transform: uppercase;
+      letter-spacing: 0.1em;
+      color: var(--muted);
+      padding-bottom: 0.4rem;
+      border-bottom: 1px solid var(--border);
+    }
+    .rd-params-wrap { max-height: 200px; overflow-y: auto; }
+    .rd-ai-box {
+      background: rgba(79,70,229,0.07);
+      border: 1px solid rgba(79,70,229,0.2);
+      border-radius: 10px;
+      padding: 0.9rem 1rem;
+      font-size: 0.78rem;
+      color: var(--text);
+      line-height: 1.7;
+    }
+    .rd-ai-analysis { color: #94a3b8; margin-bottom: 0.65rem; }
+    .rd-ai-changes { display: flex; flex-direction: column; gap: 0.35rem; }
+    .rd-ai-change {
+      display: flex; align-items: center; gap: 0.5rem;
+      font-family: 'JetBrains Mono', monospace; font-size: 0.72rem;
+    }
+    .rd-ai-change-param { color: var(--teal); }
+    .rd-ai-change-arrow { color: var(--muted); }
+    .rd-ai-change-val { color: var(--text); font-weight: 600; }
+    .run-detail-footer {
+      padding: 0.85rem 1.5rem;
+      border-top: 1px solid var(--border);
+      display: flex;
+      align-items: center;
+      justify-content: flex-end;
+      gap: 0.65rem;
+      flex-shrink: 0;
+    }
+
+    /* ── Live Intelligence (thinking / changes / validation) ──── */
+    .live-intel-row {
+      display: grid;
+      grid-template-columns: 1.1fr 1fr 1fr;
+      gap: 0.7rem;
+      flex-shrink: 0;
+    }
+    .live-intel-card {
+      background: var(--card-bg);
+      border: 1px solid var(--border);
+      border-radius: 12px;
+      padding: 0.9rem 1rem;
+      display: flex;
+      flex-direction: column;
+      min-height: 240px;
+      max-height: 280px;
+      position: relative;
+      overflow: hidden;
+    }
+    .live-intel-card.accent {
+      border-color: rgba(79,70,229,0.32);
+    }
+    .live-intel-card.accent::before {
+      content: '';
+      position: absolute;
+      top: 0; left: 0; right: 0; height: 1px;
+      background: linear-gradient(90deg, transparent, rgba(124,109,250,0.7), transparent);
+    }
+    .live-intel-title {
+      font-size: 0.78rem;
+      font-weight: 600;
+      color: var(--text);
+      display: flex;
+      align-items: center;
+      gap: 0.5rem;
+      margin-bottom: 0.65rem;
+      flex-shrink: 0;
+    }
+    .live-intel-title .icon { color: var(--accent2); }
+    .live-intel-title .badge {
+      margin-left: auto;
+      font-size: 0.6rem;
+      font-weight: 700;
+      padding: 0.12rem 0.5rem;
+      border-radius: 999px;
+      background: rgba(100,116,139,0.15);
+      color: var(--muted);
+      text-transform: uppercase;
+      letter-spacing: 0.06em;
+    }
+    .live-intel-title .badge.live {
+      background: rgba(0,212,170,0.15);
+      color: var(--teal);
+    }
+    .live-intel-title .badge.live::before {
+      content: '●';
+      margin-right: 0.25rem;
+      animation: pulse-dot 1.8s ease-in-out infinite;
+    }
+    .live-intel-body {
+      flex: 1;
+      overflow-y: auto;
+      scrollbar-width: thin;
+      scrollbar-color: rgba(255,255,255,0.1) transparent;
+    }
+    .live-intel-body::-webkit-scrollbar { width: 3px; }
+    .live-intel-body::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.08); border-radius: 999px; }
+    .live-intel-empty {
+      color: var(--muted);
+      font-size: 0.76rem;
+      padding: 1rem 0.5rem;
+      text-align: center;
+    }
+
+    /* ── Thinking feed entries ──────────────────────────────── */
+    .tf-entry {
+      display: flex;
+      gap: 0.55rem;
+      padding: 0.5rem 0.1rem;
+      border-bottom: 1px solid rgba(255,255,255,0.03);
+      font-size: 0.76rem;
+      line-height: 1.45;
+      animation: tf-slidein 0.25s ease both;
+    }
+    @keyframes tf-slidein {
+      from { opacity: 0; transform: translateY(-4px); }
+      to   { opacity: 1; transform: translateY(0); }
+    }
+    .tf-entry:last-child { border-bottom: none; }
+    .tf-marker {
+      flex-shrink: 0;
+      width: 18px;
+      text-align: center;
+      font-weight: 700;
+      font-size: 0.78rem;
+      margin-top: 0.05em;
+    }
+    .tf-entry.info      .tf-marker { color: var(--muted); }
+    .tf-entry.reasoning .tf-marker { color: var(--accent2); }
+    .tf-entry.decision  .tf-marker { color: var(--teal); }
+    .tf-entry.success   .tf-marker { color: var(--green); }
+    .tf-entry.warning   .tf-marker { color: var(--yellow); }
+    .tf-entry.hypothesis .tf-marker { color: #a78bfa; }
+    .tf-body { flex: 1; min-width: 0; }
+    .tf-msg { color: var(--text); word-wrap: break-word; }
+    .tf-entry.info .tf-msg { color: #94a3b8; }
+    .tf-entry.warning .tf-msg { color: #fbbf24; }
+    .tf-meta {
+      font-size: 0.62rem;
+      color: var(--muted);
+      margin-top: 0.15rem;
+      display: flex;
+      gap: 0.5rem;
+      font-family: 'JetBrains Mono', monospace;
+    }
+    .tf-chip {
+      display: inline-block;
+      padding: 0.05rem 0.35rem;
+      border-radius: 4px;
+      background: rgba(255,255,255,0.05);
+      color: var(--muted);
+      font-size: 0.6rem;
+      letter-spacing: 0.04em;
+    }
+
+    /* ── Parameter Changes list ─────────────────────────────── */
+    .pc-iteration {
+      border-bottom: 1px solid rgba(255,255,255,0.04);
+      padding: 0.55rem 0.1rem;
+      animation: tf-slidein 0.25s ease both;
+    }
+    .pc-iteration:last-child { border-bottom: none; }
+    .pc-iter-header {
+      display: flex;
+      align-items: center;
+      gap: 0.4rem;
+      font-size: 0.72rem;
+      color: var(--text);
+      font-weight: 600;
+      margin-bottom: 0.3rem;
+    }
+    .pc-iter-label {
+      background: rgba(79,70,229,0.15);
+      color: var(--accent2);
+      font-family: 'JetBrains Mono', monospace;
+      padding: 0.08rem 0.4rem;
+      border-radius: 4px;
+      font-size: 0.65rem;
+    }
+    .pc-iter-conf {
+      margin-left: auto;
+      font-size: 0.62rem;
+      color: var(--muted);
+    }
+    .pc-change {
+      font-size: 0.7rem;
+      line-height: 1.55;
+      padding: 0.12rem 0;
+    }
+    .pc-param { color: var(--teal); font-family: 'JetBrains Mono', monospace; }
+    .pc-arrow { color: var(--muted); margin: 0 0.3rem; }
+    .pc-oldval { color: var(--muted); font-family: 'JetBrains Mono', monospace; text-decoration: line-through; }
+    .pc-newval { color: var(--text); font-family: 'JetBrains Mono', monospace; font-weight: 600; }
+    .pc-reason { color: #94a3b8; font-size: 0.66rem; margin-left: 1.3rem; font-style: italic; }
+
+    /* ── Validation Live Panel ──────────────────────────────── */
+    .val-header {
+      font-size: 0.7rem;
+      color: var(--muted);
+      margin-bottom: 0.5rem;
+    }
+    .val-progress-row {
+      display: flex;
+      align-items: center;
+      gap: 0.45rem;
+      font-size: 0.68rem;
+      color: var(--muted);
+      margin-bottom: 0.6rem;
+    }
+    .val-progress-bar {
+      flex: 1;
+      height: 4px;
+      background: rgba(255,255,255,0.07);
+      border-radius: 999px;
+      overflow: hidden;
+    }
+    .val-progress-fill {
+      height: 100%;
+      background: linear-gradient(90deg, var(--accent), var(--teal));
+      width: 0%;
+      transition: width 0.4s ease;
+    }
+    .val-run {
+      border: 1px solid var(--border);
+      border-radius: 8px;
+      padding: 0.55rem 0.7rem;
+      margin-bottom: 0.4rem;
+      background: rgba(255,255,255,0.02);
+      animation: tf-slidein 0.25s ease both;
+    }
+    .val-run.active { border-color: rgba(0,212,170,0.4); background: rgba(0,212,170,0.04); }
+    .val-run.pass   { border-color: rgba(16,185,129,0.35); }
+    .val-run.fail   { border-color: rgba(239,68,68,0.35); }
+    .val-run-title {
+      font-size: 0.72rem;
+      font-weight: 600;
+      color: var(--text);
+      display: flex;
+      align-items: center;
+      gap: 0.4rem;
+    }
+    .val-run-kind {
+      font-size: 0.58rem;
+      font-weight: 700;
+      padding: 0.08rem 0.4rem;
+      border-radius: 4px;
+      text-transform: uppercase;
+      letter-spacing: 0.06em;
+      background: rgba(100,116,139,0.15);
+      color: var(--muted);
+    }
+    .val-run-kind.oos { background: rgba(79,70,229,0.18); color: var(--accent2); }
+    .val-run-kind.sensitivity { background: rgba(245,158,11,0.15); color: var(--yellow); }
+    .val-run-desc { font-size: 0.64rem; color: #94a3b8; margin-top: 0.2rem; line-height: 1.4; }
+    .val-run-metrics {
+      display: grid;
+      grid-template-columns: repeat(4, 1fr);
+      gap: 0.3rem;
+      margin-top: 0.4rem;
+    }
+    .val-metric { background: rgba(255,255,255,0.03); border-radius: 5px; padding: 0.25rem 0.4rem; }
+    .val-metric-lbl { font-size: 0.55rem; color: var(--muted); text-transform: uppercase; letter-spacing: 0.04em; }
+    .val-metric-val { font-size: 0.72rem; font-weight: 700; margin-top: 0.05rem; }
+    .val-spinner {
+      display: inline-block;
+      width: 10px; height: 10px;
+      border: 2px solid rgba(124,109,250,0.3);
+      border-top-color: var(--accent2);
+      border-radius: 50%;
+      animation: ai-spin 0.8s linear infinite;
+    }
+
+    /* ── Early Termination Banner ───────────────────────────── */
+    .early-term-banner {
+      display: none;
+      flex-direction: column;
+      gap: 0.35rem;
+      padding: 0.85rem 1.1rem;
+      background: rgba(245,158,11,0.08);
+      border: 1px solid rgba(245,158,11,0.28);
+      border-radius: 12px;
+      font-size: 0.82rem;
+      color: var(--yellow);
+      animation: tf-slidein 0.3s ease both;
+    }
+    .early-term-banner.active { display: flex; }
+    .early-term-banner.success { background: rgba(16,185,129,0.08); border-color: rgba(16,185,129,0.3); color: var(--green); }
+    .early-term-banner.warning { background: rgba(245,158,11,0.08); border-color: rgba(245,158,11,0.28); color: var(--yellow); }
+    .early-term-banner.critical { background: rgba(239,68,68,0.1); border-color: rgba(239,68,68,0.3); color: var(--red); }
+    .early-term-title { display: flex; align-items: center; gap: 0.55rem; font-weight: 700; }
+    .early-term-msg { font-size: 0.75rem; color: var(--text); line-height: 1.5; font-weight: 500; }
+    .early-term-details {
+      font-size: 0.7rem;
+      color: var(--muted);
+      margin-top: 0.2rem;
+      display: flex;
+      flex-wrap: wrap;
+      gap: 0.5rem 1rem;
+    }
+    .early-term-dismiss {
+      background: transparent;
+      border: none;
+      color: var(--muted);
+      cursor: pointer;
+      margin-left: auto;
+      font-size: 1rem;
+      line-height: 1;
+      padding: 0;
+    }
+    .early-term-dismiss:hover { color: var(--text); }
+
+    /* ── Phase tracker (enhanced) ───────────────────────────── */
+    .phase-step .phase-sub {
+      font-size: 0.55rem;
+      color: var(--muted);
+      margin-top: 0.1rem;
+      text-align: center;
+      font-family: 'JetBrains Mono', monospace;
+      line-height: 1;
+    }
+    .phase-step.active .phase-sub { color: var(--teal); }
   </style>
 </head>
 <body>
 
-  <!-- ── HEADER ── -->
-  <header class="header">
-    <div class="header-left">
-      <div class="logo">
-        <span class="logo-icon">⚡</span>
+<div class="app-shell">
+
+  <!-- ══════════════════════════════════════
+       SIDEBAR
+  ══════════════════════════════════════ -->
+  <aside class="sidebar">
+
+    <!-- Logo -->
+    <div class="logo-wrap">
+      <svg width="36" height="40" viewBox="0 0 40 44" fill="none" xmlns="http://www.w3.org/2000/svg">
+        <defs>
+          <linearGradient id="logoGrad" x1="0%" y1="0%" x2="100%" y2="100%">
+            <stop offset="0%" stop-color="#00e5ff"/>
+            <stop offset="45%" stop-color="#4f46e5"/>
+            <stop offset="100%" stop-color="#7c3aed"/>
+          </linearGradient>
+          <clipPath id="sbTriClip">
+            <polygon points="20,2 39,40 1,40"/>
+          </clipPath>
+        </defs>
+        <polygon points="20,2 39,40 1,40" fill="rgba(79,70,229,0.08)" stroke="url(#logoGrad)" stroke-width="2" stroke-linejoin="round"/>
+        <line x1="10" y1="30" x2="30" y2="30" stroke="url(#logoGrad)" stroke-width="1.5"/>
+        <rect x="11" y="31" width="4" height="8" rx="0.8" fill="url(#logoGrad)" opacity="0.5" clip-path="url(#sbTriClip)"/>
+        <rect x="17" y="24" width="4" height="15" rx="0.8" fill="url(#logoGrad)" opacity="0.75" clip-path="url(#sbTriClip)"/>
+        <rect x="23" y="18" width="4" height="21" rx="0.8" fill="url(#logoGrad)" clip-path="url(#sbTriClip)"/>
+        <polyline points="8,38 17,27 22,30 33,16" stroke="#00e5ff" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" clip-path="url(#sbTriClip)" opacity="0.9"/>
+      </svg>
+      <div>
+        <span class="logo-text">APEX</span>
+        <span class="logo-tagline">AI Optimizer</span>
+      </div>
+    </div>
+
+    <!-- Navigation -->
+    <nav class="sidebar-nav">
+
+      <a href="/dashboard" class="nav-item active" data-page="dashboard">
+        <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
+          <path d="M3 9l9-7 9 7v11a2 2 0 01-2 2H5a2 2 0 01-2-2z"/><polyline points="9 22 9 12 15 12 15 22"/>
+        </svg>
+        Dashboard
+      </a>
+
+      <a href="/setup" class="nav-item" data-page="setup">
+        <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
+          <line x1="4" y1="21" x2="4" y2="14"/><line x1="4" y1="10" x2="4" y2="3"/>
+          <line x1="12" y1="21" x2="12" y2="12"/><line x1="12" y1="8" x2="12" y2="3"/>
+          <line x1="20" y1="21" x2="20" y2="16"/><line x1="20" y1="12" x2="20" y2="3"/>
+          <line x1="1" y1="14" x2="7" y2="14"/><line x1="9" y1="8" x2="15" y2="8"/><line x1="17" y1="16" x2="23" y2="16"/>
+        </svg>
+        New Run
+      </a>
+
+      <a href="/reports" class="nav-item" data-page="reports">
+        <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
+          <line x1="18" y1="20" x2="18" y2="10"/><line x1="12" y1="20" x2="12" y2="4"/>
+          <line x1="6" y1="20" x2="6" y2="14"/><line x1="2" y1="20" x2="22" y2="20"/>
+        </svg>
+        Reports
+      </a>
+
+      <a href="https://github.com/your-user/MT5_Optimizer" target="_blank" rel="noopener" class="nav-item" data-page="github">
+        <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
+          <path d="M9 19c-5 1.5-5-2.5-7-3m14 6v-3.87a3.37 3.37 0 0 0-.94-2.61c3.14-.35 6.44-1.54 6.44-7A5.44 5.44 0 0 0 20 4.77 5.07 5.07 0 0 0 19.91 1S18.73.65 16 2.48a13.38 13.38 0 0 0-7 0C6.27.65 5.09 1 5.09 1A5.07 5.07 0 0 0 5 4.77a5.44 5.44 0 0 0-1.5 3.78c0 5.42 3.3 6.61 6.44 7A3.37 3.37 0 0 0 9 18.13V22"/>
+        </svg>
+        Source on GitHub
+      </a>
+
+      <a href="#" class="nav-item" data-page="set" onclick="openSettings(); return false;">
+        <!-- Gear icon -->
+        <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
+          <circle cx="12" cy="12" r="3"/>
+          <path d="M19.4 15a1.65 1.65 0 00.33 1.82l.06.06a2 2 0 010 2.83 2 2 0 01-2.83 0l-.06-.06a1.65 1.65 0 00-1.82-.33 1.65 1.65 0 00-1 1.51V21a2 2 0 01-2 2 2 2 0 01-2-2v-.09A1.65 1.65 0 009 19.4a1.65 1.65 0 00-1.82.33l-.06.06a2 2 0 01-2.83 0 2 2 0 010-2.83l.06-.06A1.65 1.65 0 004.68 15a1.65 1.65 0 00-1.51-1H3a2 2 0 01-2-2 2 2 0 012-2h.09A1.65 1.65 0 004.6 9a1.65 1.65 0 00-.33-1.82l-.06-.06a2 2 0 010-2.83 2 2 0 012.83 0l.06.06A1.65 1.65 0 009 4.68a1.65 1.65 0 001-1.51V3a2 2 0 012-2 2 2 0 012 2v.09a1.65 1.65 0 001 1.51 1.65 1.65 0 001.82-.33l.06-.06a2 2 0 012.83 0 2 2 0 010 2.83l-.06.06A1.65 1.65 0 0019.4 9a1.65 1.65 0 001.51 1H21a2 2 0 012 2 2 2 0 01-2 2h-.09a1.65 1.65 0 00-1.51 1z"/>
+        </svg>
+        Settings
+      </a>
+
+    </nav>
+
+    <!-- Footer: MT5 status -->
+    <div class="sidebar-footer">
+      <div class="mt5-status">
+        <div class="mt5-dot" id="mt5-dot"></div>
         <div>
-          <div class="logo-title">MT5 Smart Optimizer</div>
-          <div class="logo-sub" id="session-label">Live Dashboard</div>
+          <div class="mt5-label">MT5 Connection</div>
+          <div class="mt5-state" id="mt5-state">Ready</div>
         </div>
       </div>
+      <div class="mt5-brand">
+        <svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
+          <rect x="2" y="3" width="20" height="14" rx="2"/><line x1="8" y1="21" x2="16" y2="21"/><line x1="12" y1="17" x2="12" y2="21"/>
+        </svg>
+        MetaTrader 5
+      </div>
     </div>
-    <div class="header-center">
-      <div class="stat-pill" id="pill-state">
-        <span class="dot dot-idle" id="state-dot"></span>
-        <span id="state-label">Ready</span>
+
+  </aside>
+
+  <!-- ══════════════════════════════════════
+       MAIN CONTENT
+  ══════════════════════════════════════ -->
+  <div class="main-content" id="main-content">
+
+    <!-- ── Command Header ────────────────────────────────────── -->
+    <div class="cmd-header">
+
+      <!-- Logo -->
+      <div class="cmd-logo">
+        <svg width="32" height="36" viewBox="0 0 40 44" fill="none" xmlns="http://www.w3.org/2000/svg">
+          <defs>
+            <linearGradient id="hdrLogoGrad" x1="0%" y1="0%" x2="100%" y2="100%">
+              <stop offset="0%" stop-color="#00e5ff"/>
+              <stop offset="45%" stop-color="#4f46e5"/>
+              <stop offset="100%" stop-color="#7c3aed"/>
+            </linearGradient>
+            <clipPath id="hdrTriClip">
+              <polygon points="20,2 39,40 1,40"/>
+            </clipPath>
+          </defs>
+          <polygon points="20,2 39,40 1,40" fill="rgba(79,70,229,0.09)" stroke="url(#hdrLogoGrad)" stroke-width="1.8" stroke-linejoin="round"/>
+          <line x1="10" y1="30" x2="30" y2="30" stroke="url(#hdrLogoGrad)" stroke-width="1.4"/>
+          <rect x="11" y="31" width="4" height="8" rx="0.8" fill="url(#hdrLogoGrad)" opacity="0.5" clip-path="url(#hdrTriClip)"/>
+          <rect x="17" y="24" width="4" height="15" rx="0.8" fill="url(#hdrLogoGrad)" opacity="0.75" clip-path="url(#hdrTriClip)"/>
+          <rect x="23" y="18" width="4" height="21" rx="0.8" fill="url(#hdrLogoGrad)" clip-path="url(#hdrTriClip)"/>
+          <polyline points="8,38 17,27 22,30 33,16" stroke="#00e5ff" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" clip-path="url(#hdrTriClip)" opacity="0.9"/>
+        </svg>
+        <div class="cmd-logo-text">
+          <span class="cmd-apex">APEX</span>
+          <span class="cmd-tagline">AI Powered EA Optimizer</span>
+        </div>
       </div>
-      <div class="stat-pill">
-        <span class="pill-label">Runs</span>
-        <span class="pill-val" id="hdr-iter">0</span>
+
+      <div class="cmd-sep"></div>
+
+      <!-- Status -->
+      <div class="cmd-section">
+        <div class="cmd-status-row">
+          <div class="cmd-status-dot" id="hdr-dot"></div>
+          <span class="cmd-status-label" id="hdr-status">System Idle</span>
+        </div>
+        <div class="cmd-section-sub" id="hdr-status-sub">Ready to optimize</div>
       </div>
-      <div class="stat-pill">
-        <span class="pill-label">Best Score</span>
-        <span class="pill-val score-val" id="hdr-score">—</span>
+
+      <div class="cmd-sep"></div>
+
+      <!-- Generation / Progress -->
+      <div class="cmd-section cmd-gen-section">
+        <div class="cmd-gen-row">
+          <span class="cmd-gen-label">Generation</span>
+          <span class="cmd-gen-val"><span id="hdr-gen-cur">0</span><span class="cmd-gen-sep">/</span><span id="hdr-gen-total">—</span></span>
+        </div>
+        <div class="cmd-prog-track">
+          <div class="cmd-prog-fill" id="hdr-prog-fill" style="width:0%"></div>
+        </div>
+        <div class="cmd-pct-label" id="hdr-pct">0% Complete</div>
       </div>
-      <div class="stat-pill">
-        <span class="pill-label">Elapsed</span>
-        <span class="pill-val" id="hdr-elapsed">0:00</span>
+
+      <div class="cmd-sep"></div>
+
+      <!-- Best Score -->
+      <div class="cmd-section">
+        <div class="cmd-score-label">Best Score</div>
+        <div class="cmd-score-val" id="hdr-score">—</div>
+        <div class="cmd-score-delta" id="hdr-score-delta">Waiting for results...</div>
+      </div>
+
+      <div class="cmd-spacer"></div>
+
+      <!-- Action buttons -->
+      <div class="cmd-actions">
+        <a href="/setup" class="cmd-btn cmd-btn-start">
+          <svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2.5"><line x1="12" y1="5" x2="12" y2="19"/><line x1="5" y1="12" x2="19" y2="12"/></svg>
+          Start New
+        </a>
+        <!-- Pause is intentionally not shown — pipeline doesn't currently support it
+             (see: optimizer/pipeline.py — only _stop_flag exists, no _pause_event). -->
+        <button class="cmd-btn cmd-btn-stop" id="btn-stop">
+          <svg width="12" height="12" viewBox="0 0 24 24" fill="currentColor"><rect x="4" y="4" width="16" height="16" rx="2"/></svg>
+          Stop
+        </button>
+      </div>
+
+      <!-- Hidden run-indicator kept for JS compatibility -->
+      <div id="run-indicator" style="display:none!important;"><span id="run-indicator-label"></span></div>
+
+    </div>
+
+    <!-- No-profit error banner -->
+    <div class="no-profit-banner" id="no-profit-banner">
+      <span class="no-profit-banner-icon">⚠</span>
+      <div>
+        <strong>No profitable configuration found.</strong>
+        <span id="no-profit-msg"> Try different parameters or date ranges.</span>
       </div>
     </div>
-    <div class="header-right">
-      <a href="/" class="btn btn-secondary">🏠 Home</a>
-      <a href="/reports" class="btn btn-secondary">📁 Reports</a>
-      <button class="btn btn-stop hidden" id="btn-stop" onclick="stopOptimizer()">⏹ Stop</button>
-      <a href="/setup" class="btn btn-start" id="btn-start">⚡ New Run</a>
+
+    <!-- Early Termination banner (dismissible) -->
+    <div class="early-term-banner" id="early-term-banner">
+      <div class="early-term-title">
+        <span id="early-term-icon">⚠</span>
+        <span id="early-term-heading">Optimization stopped early</span>
+        <button class="early-term-dismiss" onclick="dismissEarlyTerm()">✕</button>
+      </div>
+      <div class="early-term-msg" id="early-term-msg"></div>
+      <div class="early-term-details" id="early-term-details"></div>
     </div>
-  </header>
 
-  <!-- ── MAIN GRID ── -->
-  <main class="main-grid">
+    <!-- ── Metric cards ────────────────────────────────────────── -->
+    <div class="metrics-row">
 
-    <!-- LEFT COLUMN -->
-    <div class="col-left">
-
-      <!-- Verdict banner (hidden until complete) -->
-      <div class="verdict-banner" id="verdict-banner"></div>
-
-      <!-- No-profit warning (hidden until needed) -->
-      <div class="no-profit-banner" id="no-profit-banner">
-        <h3>⚠️ No Profitable Configuration Found</h3>
-        <p id="no-profit-msg">Phase 1 found no profitable configuration. Try a different timeframe, date range, or check EA settings.</p>
-        <div style="margin-top:1rem">
-          <a href="/setup" class="btn-new-run">⚡ Try Again with Different Settings</a>
+      <!-- Net Profit (clickable → Best Result detail) -->
+      <div class="metric-card" id="best-card" onclick="openBestResult()" style="cursor:pointer" title="Click to see how the AI arrived at this best result">
+        <div class="metric-label">Best Net Profit <span style="font-size:0.55rem;color:var(--accent2);font-weight:700">▸ details</span></div>
+        <div class="metric-value green" id="m-net-profit">$0.00</div>
+        <div class="metric-delta" id="m-net-profit-delta">
+          <span class="delta-up">↑</span>
+          <span id="m-net-profit-delta-val">0%</span>
+          <span style="margin-left:2px">vs baseline</span>
+        </div>
+        <div class="sparkline-wrap">
+          <canvas id="spark-profit" width="80" height="28"></canvas>
         </div>
       </div>
 
-      <!-- Progress -->
-      <div class="progress-wrap" id="progress-wrap" style="display:none">
-        <div class="progress-header">
-          <span class="progress-phase" id="progress-phase">Phase 1: Broad Discovery</span>
-          <span class="progress-count" id="progress-count">0 / 0</span>
+      <!-- Max Drawdown -->
+      <div class="metric-card">
+        <div class="metric-label">Max Drawdown</div>
+        <div class="metric-value red" id="m-max-dd">0.00%</div>
+        <div class="metric-delta" id="m-max-dd-delta">
+          <span class="delta-down">↓</span>
+          <span id="m-max-dd-delta-val">0%</span>
+          <span style="margin-left:2px">vs baseline</span>
         </div>
-        <div class="progress-bar-track">
-          <div class="progress-bar-fill" id="progress-bar-fill"></div>
-        </div>
-        <div class="progress-budget" id="progress-budget"></div>
-      </div>
-
-      <!-- Score Chart -->
-      <div class="card">
-        <div class="card-header">
-          <span class="card-title">📈 Score History</span>
-          <span class="card-badge" id="chart-badge">Waiting...</span>
-        </div>
-        <div class="chart-wrap">
-          <canvas id="scoreChart"></canvas>
+        <div class="sparkline-wrap">
+          <canvas id="spark-dd" width="80" height="28"></canvas>
         </div>
       </div>
 
-      <!-- Current Run Metrics -->
-      <div class="card">
-        <div class="card-header">
-          <span class="card-title">🎯 Latest Run Metrics</span>
-          <span class="run-id-badge" id="current-run-id">—</span>
+      <!-- Profit Factor -->
+      <div class="metric-card">
+        <div class="metric-label">Profit Factor</div>
+        <div class="metric-value gold" id="m-pf">0.00</div>
+        <div class="metric-delta">
+          <span id="m-pf-quality" style="color:var(--muted)">—</span>
         </div>
-        <div class="metrics-grid">
-          <div class="metric-card"><div class="metric-label">Net Profit</div><div class="metric-val" id="m-profit">—</div></div>
-          <div class="metric-card"><div class="metric-label">Calmar Ratio</div><div class="metric-val" id="m-calmar">—</div></div>
-          <div class="metric-card"><div class="metric-label">Profit Factor</div><div class="metric-val" id="m-pf">—</div></div>
-          <div class="metric-card"><div class="metric-label">Max Drawdown</div><div class="metric-val" id="m-dd">—</div></div>
-          <div class="metric-card"><div class="metric-label">Win Rate</div><div class="metric-val" id="m-wr">—</div></div>
-          <div class="metric-card"><div class="metric-label">Total Trades</div><div class="metric-val" id="m-trades">—</div></div>
+        <div class="sparkline-wrap">
+          <canvas id="spark-pf" width="80" height="28"></canvas>
         </div>
-        <div class="score-bar-wrap">
-          <div class="score-bar-label">
-            <span>Session Score</span>
-            <span class="score-big" id="m-score">—</span>
+      </div>
+
+      <!-- Total Trades -->
+      <div class="metric-card">
+        <div class="metric-label">Total Trades</div>
+        <div class="metric-value teal" id="m-trades">0</div>
+        <div class="metric-delta">
+          <span style="color:var(--muted)">This run</span>
+        </div>
+        <div class="sparkline-wrap">
+          <canvas id="spark-trades" width="80" height="28"></canvas>
+        </div>
+      </div>
+
+      <!-- Optimization Runs -->
+      <div class="metric-card">
+        <div class="metric-label">Optimization Runs</div>
+        <div class="metric-value white" id="m-runs">0</div>
+        <div class="metric-delta">
+          <span style="color:var(--muted)">This session</span>
+        </div>
+        <div class="sparkline-wrap">
+          <canvas id="spark-runs" width="80" height="28"></canvas>
+        </div>
+      </div>
+
+      <!-- AI Confidence (special) -->
+      <div class="metric-card ai-conf-card">
+        <div class="metric-label">AI Confidence</div>
+        <div class="ai-conf-value" id="ai-conf-label">—</div>
+        <div class="ai-gauge-wrap">
+          <svg id="ai-gauge" width="60" height="60" viewBox="0 0 64 64">
+            <circle cx="32" cy="32" r="26" fill="none" stroke="rgba(255,255,255,0.07)" stroke-width="6"/>
+            <circle id="ai-gauge-arc" cx="32" cy="32" r="26" fill="none"
+              stroke="#00d4aa" stroke-width="6" stroke-linecap="round"
+              stroke-dasharray="163.4" stroke-dashoffset="163.4"
+              transform="rotate(-90 32 32)"
+              style="transition: stroke-dashoffset 1s ease, stroke 0.5s ease"/>
+            <text id="ai-gauge-pct" x="32" y="37" text-anchor="middle"
+              fill="#e2e8f0" font-size="12" font-weight="700" font-family="Inter, sans-serif">0%</text>
+          </svg>
+        </div>
+      </div>
+
+    </div>
+
+    <!-- ── Charts + AI panel ────────────────────────────────────── -->
+    <div class="charts-ai-row">
+
+      <!-- Left: charts column -->
+      <div class="charts-col">
+
+        <!-- Equity Curve -->
+        <div class="card">
+          <div class="card-header">
+            <div class="card-title">
+              <div class="dot"></div>
+              Equity Curve
+            </div>
+            <div style="display:flex;gap:0.6rem;align-items:center;">
+              <span style="font-size:0.68rem;color:var(--muted);display:flex;align-items:center;gap:0.3rem;">
+                <span style="display:inline-block;width:20px;height:2px;background:#4f46e5;border-radius:2px;"></span> Equity
+              </span>
+              <span style="font-size:0.68rem;color:var(--muted);display:flex;align-items:center;gap:0.3rem;">
+                <span style="display:inline-block;width:20px;height:2px;background:#00d4aa;border-radius:2px;border-bottom:2px dashed #00d4aa;height:0;"></span> Balance
+              </span>
+              <div class="card-badge" id="equity-badge">Live</div>
+            </div>
           </div>
-          <div class="score-bar-track">
-            <div class="score-bar-fill" id="score-bar-fill" style="width:0%"></div>
+          <div class="chart-wrap equity-chart-wrap">
+            <canvas id="equityChart"></canvas>
+          </div>
+        </div>
+
+        <!-- Drawdown Chart -->
+        <div class="card">
+          <div class="card-header">
+            <div class="card-title">
+              <div class="dot" style="background:var(--red);"></div>
+              Drawdown Analysis
+            </div>
+            <span class="card-badge" id="max-dd-badge" style="background:rgba(239,68,68,0.12);color:var(--red);">Max DD: 0%</span>
+          </div>
+          <div class="chart-wrap drawdown-chart-wrap">
+            <canvas id="drawdownChart"></canvas>
+          </div>
+        </div>
+
+      </div>
+
+      <!-- Right: AI panel -->
+      <div class="ai-panel-col">
+        <div class="ai-panel-card" id="ai-panel">
+          <div class="ai-panel-header">
+            <div class="ai-panel-title">
+              <span class="ai-icon">✦</span>
+              AI Summary
+            </div>
+            <a href="#" class="view-details-link" id="ai-view-details" onclick="toggleAIDetails(); return false;">View Details →</a>
+          </div>
+
+          <!-- Waiting state -->
+          <div class="ai-waiting" id="ai-waiting">
+            <div class="ai-pulse-dot"></div>
+            <span>Waiting for optimization to start...</span>
+          </div>
+
+          <!-- Active state -->
+          <div class="ai-content" id="ai-content" style="display:none;">
+
+            <!-- Collapsed preview (always shown when data loaded) -->
+            <div class="ai-preview" id="ai-preview">
+              <div class="ai-headline" id="ai-headline" style="display:none;"></div>
+              <p class="ai-diagnosis" id="ai-diagnosis-text">—</p>
+              <button class="ai-expand-btn" id="ai-expand-btn" onclick="toggleAIDetails()">View Details →</button>
+            </div>
+
+            <!-- Expanded details (hidden by default) -->
+            <div class="ai-details" id="ai-details">
+              <div id="ai-strengths-section" style="display:none;">
+                <div class="ai-sub-title">Top Patterns</div>
+                <ul class="ai-check-list" id="ai-strengths-list"></ul>
+              </div>
+
+              <div class="ai-suggestion-box" id="ai-suggestion-box" style="display:none;">
+                <div class="ai-sub-title" style="margin-bottom:0.3rem;">Key Suggestion</div>
+                <p class="ai-suggestion-text" id="ai-suggestion-text"></p>
+                <div class="ai-badge">AI</div>
+              </div>
+
+              <div id="ai-risks-section" style="display:none;">
+                <div class="ai-sub-title warn">Risk Flags</div>
+                <ul class="ai-warn-list" id="ai-risks-list"></ul>
+              </div>
+            </div>
+
+            <div class="ai-confidence-row">
+              <span class="ai-conf-badge" id="ai-panel-conf-badge">analyzing</span>
+              <span class="ai-run-ref" id="ai-run-ref"></span>
+            </div>
+
           </div>
         </div>
       </div>
 
     </div>
 
-    <!-- RIGHT COLUMN -->
-    <div class="col-right">
+    <!-- ── Live Intelligence (thinking feed / param changes / validation) ── -->
+    <div class="live-intel-row">
 
-      <!-- Phase steps -->
-      <div class="card phase-card">
-        <div class="phase-steps">
-          <div class="phase-step" id="phase-setup">
-            <div class="phase-dot">1</div>
-            <div class="phase-name">Setup</div>
-          </div>
-          <div class="phase-line"></div>
-          <div class="phase-step" id="phase-phase1">
-            <div class="phase-dot">2</div>
-            <div class="phase-name">Broad Search</div>
-          </div>
-          <div class="phase-line"></div>
-          <div class="phase-step" id="phase-phase2">
-            <div class="phase-dot">3</div>
-            <div class="phase-name">Refine</div>
-          </div>
-          <div class="phase-line"></div>
-          <div class="phase-step" id="phase-phase3">
-            <div class="phase-dot">4</div>
-            <div class="phase-name">Validate</div>
-          </div>
-          <div class="phase-line"></div>
-          <div class="phase-step" id="phase-done">
-            <div class="phase-dot">✓</div>
-            <div class="phase-name">Done</div>
-          </div>
+      <!-- AI Thinking Feed -->
+      <div class="live-intel-card accent">
+        <div class="live-intel-title">
+          <span class="icon">✦</span>
+          AI Thinking
+          <span class="badge" id="tf-badge">Idle</span>
+        </div>
+        <div class="live-intel-body" id="thinking-feed">
+          <div class="live-intel-empty">Waiting for the optimizer to start…<br><span style="font-size:0.68rem">The AI's reasoning will stream here in real time.</span></div>
         </div>
       </div>
 
-      <!-- Phase 1 results table -->
-      <div class="card" id="phase1-results-card" style="display:none">
-        <div class="card-header">
-          <span class="card-title">🏆 Phase 1 — Top Configurations</span>
-          <span class="card-badge" id="phase1-badge">—</span>
+      <!-- Parameter Changes -->
+      <div class="live-intel-card">
+        <div class="live-intel-title">
+          <svg class="icon" width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><polyline points="22 12 18 12 15 21 9 3 6 12 2 12"/></svg>
+          Parameter Changes
+          <span class="badge" id="pc-badge">—</span>
         </div>
-        <div class="results-table-wrap">
-          <table class="results-table">
+        <div class="live-intel-body" id="param-changes-list">
+          <div class="live-intel-empty">No iterations yet.<br><span style="font-size:0.68rem">AI-driven parameter edits appear per iteration.</span></div>
+        </div>
+      </div>
+
+      <!-- Validation Activity -->
+      <div class="live-intel-card">
+        <div class="live-intel-title">
+          <svg class="icon" width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M12 22s8-4 8-10V5l-8-3-8 3v7c0 6 8 10 8 10z"/></svg>
+          Validation
+          <span class="badge" id="val-badge">Pending</span>
+        </div>
+        <div class="live-intel-body" id="validation-panel">
+          <div class="live-intel-empty">Validation runs after optimization.<br><span style="font-size:0.68rem">Out-of-sample + sensitivity tests.</span></div>
+        </div>
+      </div>
+
+    </div>
+
+    <!-- ── Bottom row ───────────────────────────────────────────── -->
+    <div class="bottom-row">
+
+      <!-- Top Parameters -->
+      <div class="bottom-card">
+        <div class="bottom-card-title">
+          Top Parameters
+          <span style="font-size:0.65rem;color:var(--muted);font-weight:400;">(Best Run)</span>
+        </div>
+        <div style="overflow-x:auto;flex:1;">
+          <table class="params-table" id="params-table">
             <thead>
               <tr>
-                <th>#</th>
-                <th>Profit</th>
-                <th>Calmar</th>
-                <th>PF</th>
-                <th>Win%</th>
-                <th>DD%</th>
-                <th>Trades</th>
-                <th>Score</th>
+                <th>Parameter</th>
+                <th>Value</th>
+                <th>Impact</th>
               </tr>
             </thead>
-            <tbody id="phase1-tbody"></tbody>
+            <tbody id="params-tbody">
+              <tr><td colspan="3" class="empty-state">Run optimizer to see parameters</td></tr>
+            </tbody>
           </table>
         </div>
       </div>
 
-      <!-- Live log -->
-      <div class="card log-card">
-        <div class="card-header">
-          <span class="card-title">📋 Live Log</span>
-          <button class="clear-btn" onclick="clearLog()">Clear</button>
-        </div>
-        <div class="log-feed" id="log-feed">
-          <div class="log-line log-info">System ready. <a href="/setup" style="color:inherit;opacity:0.7">Start a new optimization →</a></div>
+      <!-- Optimization Progress -->
+      <div class="bottom-card">
+        <div class="bottom-card-title">Optimization Progress</div>
+        <div style="display:flex;flex-direction:column;gap:0.5rem;flex:1;">
+          <div class="opt-gen-label" id="opt-gen">Generation — / —</div>
+          <div class="opt-progress-bar-track">
+            <div class="opt-progress-bar-fill" id="opt-progress-fill" style="width:0%"></div>
+          </div>
+          <div class="opt-stats-grid">
+            <div class="opt-stat">
+              <div class="opt-stat-label">Current Phase</div>
+              <div class="opt-stat-val" id="opt-phase">Waiting</div>
+            </div>
+            <div class="opt-stat">
+              <div class="opt-stat-label">Elapsed</div>
+              <div class="opt-stat-val" id="opt-elapsed">—</div>
+            </div>
+            <div class="opt-stat">
+              <div class="opt-stat-label">Est. Remaining</div>
+              <div class="opt-stat-val" id="opt-remaining">—</div>
+            </div>
+          </div>
+          <!-- Phase steps -->
+          <div class="phase-steps" id="phase-steps">
+            <div class="phase-step" id="phase-step-1">
+              <div class="phase-dot">1</div>
+              <div class="phase-name">Exploration</div>
+              <div class="phase-sub" id="phase-sub-1">—</div>
+            </div>
+            <div class="phase-connector"></div>
+            <div class="phase-step" id="phase-step-2">
+              <div class="phase-dot">2</div>
+              <div class="phase-name">Iteration</div>
+              <div class="phase-sub" id="phase-sub-2">—</div>
+            </div>
+            <div class="phase-connector"></div>
+            <div class="phase-step" id="phase-step-3">
+              <div class="phase-dot">3</div>
+              <div class="phase-name">Validation</div>
+              <div class="phase-sub" id="phase-sub-3">—</div>
+            </div>
+          </div>
         </div>
       </div>
 
-      <!-- Best candidates so far -->
-      <div class="card candidates-card">
-        <div class="card-header">
-          <span class="card-title">⭐ Best Configs Found</span>
-          <span class="card-badge" id="cand-count">0 configs</span>
+      <!-- Recent Runs -->
+      <div class="bottom-card">
+        <div class="bottom-card-title">
+          Recent Runs
+          <a href="/reports" class="view-all-link">View All →</a>
         </div>
-        <div class="candidates-list" id="candidates-list">
-          <div class="cand-empty">Profitable configurations will appear here as the optimizer runs...</div>
+        <div style="overflow-x:auto;flex:1;">
+          <table class="runs-table">
+            <thead>
+              <tr>
+                <th>Run</th>
+                <th>Net Profit</th>
+                <th>PF</th>
+                <th>Max DD</th>
+                <th>Verdict</th>
+                <th></th>
+              </tr>
+            </thead>
+            <tbody id="recent-runs-tbody">
+              <tr><td colspan="6" class="empty-state">No runs yet</td></tr>
+            </tbody>
+          </table>
         </div>
       </div>
 
     </div>
-  </main>
 
-  <!-- ── SCRIPTS ── -->
-  <script src="https://cdn.socket.io/4.7.2/socket.io.min.js"></script>
-  <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
-  <script src="/static/js/dashboard.js"></script>
+    <!-- ── Live log (collapsible) ───────────────────────────────── -->
+    <div class="log-panel">
+      <button class="log-toggle-btn" id="log-toggle-btn" onclick="toggleLog()">
+        <span style="display:flex;align-items:center;gap:0.5rem;">
+          <svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><polyline points="4 17 10 11 4 5"/><line x1="12" y1="19" x2="20" y2="19"/></svg>
+          Live Log
+          <span id="log-count" style="background:rgba(100,116,139,0.2);color:var(--muted);font-size:0.65rem;padding:0.05rem 0.4rem;border-radius:999px;font-weight:600;">0</span>
+        </span>
+        <svg class="log-toggle-icon" id="log-toggle-icon" width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><polyline points="6 9 12 15 18 9"/></svg>
+      </button>
+      <div class="log-body" id="log-body">
+        <div class="log-feed" id="log-feed"></div>
+      </div>
+    </div>
+
+  </div><!-- /.main-content -->
+
+</div><!-- /.app-shell -->
+
+<!-- ══════════════════════════════════════
+     SETTINGS MODAL
+══════════════════════════════════════ -->
+<div class="settings-overlay" id="settings-overlay" style="display:none;" onclick="if(event.target===this)closeSettings()">
+  <div class="settings-card">
+
+    <div class="settings-header">
+      <div class="settings-title">
+        <svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
+          <circle cx="12" cy="12" r="3"/>
+          <path d="M19.4 15a1.65 1.65 0 00.33 1.82l.06.06a2 2 0 010 2.83 2 2 0 01-2.83 0l-.06-.06a1.65 1.65 0 00-1.82-.33 1.65 1.65 0 00-1 1.51V21a2 2 0 01-2 2 2 2 0 01-2-2v-.09A1.65 1.65 0 009 19.4a1.65 1.65 0 00-1.82.33l-.06.06a2 2 0 01-2.83 0 2 2 0 010-2.83l.06-.06A1.65 1.65 0 004.68 15a1.65 1.65 0 00-1.51-1H3a2 2 0 01-2-2 2 2 0 012-2h.09A1.65 1.65 0 004.6 9a1.65 1.65 0 00-.33-1.82l-.06-.06a2 2 0 010-2.83 2 2 0 012.83 0l.06.06A1.65 1.65 0 009 4.68a1.65 1.65 0 001-1.51V3a2 2 0 012-2 2 2 0 012 2v.09a1.65 1.65 0 001 1.51 1.65 1.65 0 001.82-.33l.06-.06a2 2 0 012.83 0 2 2 0 010 2.83l-.06.06A1.65 1.65 0 0019.4 9a1.65 1.65 0 001.51 1H21a2 2 0 012 2 2 2 0 01-2 2h-.09a1.65 1.65 0 00-1.51 1z"/>
+        </svg>
+        Settings
+      </div>
+      <button class="settings-close-btn" onclick="closeSettings()">✕</button>
+    </div>
+
+    <div class="settings-tabs">
+      <div class="settings-tab active" data-tab="ai" onclick="switchSettingsTab('ai')">
+        <svg width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><polygon points="13 2 3 14 12 14 11 22 21 10 12 10 13 2"/></svg>
+        AI Engine
+      </div>
+      <div class="settings-tab" data-tab="mt5" onclick="switchSettingsTab('mt5')">
+        <svg width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><rect x="2" y="3" width="20" height="14" rx="2"/><line x1="8" y1="21" x2="16" y2="21"/><line x1="12" y1="17" x2="12" y2="21"/></svg>
+        MetaTrader 5
+      </div>
+      <div class="settings-tab" data-tab="broker" onclick="switchSettingsTab('broker')">
+        <svg width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><line x1="12" y1="1" x2="12" y2="23"/><path d="M17 5H9.5a3.5 3.5 0 000 7h5a3.5 3.5 0 010 7H6"/></svg>
+        Broker
+      </div>
+      <div class="settings-tab" data-tab="thresholds" onclick="switchSettingsTab('thresholds')">
+        <svg width="13" height="13" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><line x1="4" y1="21" x2="4" y2="14"/><line x1="4" y1="10" x2="4" y2="3"/><line x1="12" y1="21" x2="12" y2="12"/><line x1="12" y1="8" x2="12" y2="3"/><line x1="20" y1="21" x2="20" y2="16"/><line x1="20" y1="12" x2="20" y2="3"/><line x1="1" y1="14" x2="7" y2="14"/><line x1="9" y1="8" x2="15" y2="8"/><line x1="17" y1="16" x2="23" y2="16"/></svg>
+        Thresholds
+      </div>
+    </div>
+
+    <div class="settings-body">
+
+      <!-- AI Engine tab -->
+      <div class="settings-panel active" id="stab-ai">
+        <div class="settings-section-label">AI Analysis Engine</div>
+        <div class="settings-toggle-row" style="margin-bottom:0.75rem;">
+          <div>
+            <div class="settings-toggle-label">Enable AI Insights</div>
+            <div class="settings-toggle-sub">Claude analyzes each run and provides actionable suggestions</div>
+          </div>
+          <button class="settings-toggle" id="s-ai-enabled" onclick="toggleSettingsBool(this)"></button>
+        </div>
+        <div class="settings-grid full">
+          <div class="settings-field">
+            <label>Anthropic API Key</label>
+            <input type="password" class="settings-input mono" id="s-ai-key" placeholder="sk-ant-api03-..." autocomplete="off">
+            <div class="settings-hint">Your Claude API key from console.anthropic.com. Kept locally in config.yaml.</div>
+          </div>
+        </div>
+        <div class="settings-grid" style="margin-top:0.75rem;">
+          <div class="settings-field">
+            <label>Model</label>
+            <select class="settings-select" id="s-ai-model">
+              <option value="claude-opus-4-7">claude-opus-4-7 (Most capable)</option>
+              <option value="claude-sonnet-4-6">claude-sonnet-4-6 (Balanced)</option>
+              <option value="claude-haiku-4-5-20251001">claude-haiku-4-5 (Fast)</option>
+            </select>
+          </div>
+          <div class="settings-field">
+            <label>Timeout (seconds)</label>
+            <input type="number" class="settings-input" id="s-ai-timeout" min="10" max="120" step="5">
+          </div>
+        </div>
+      </div>
+
+      <!-- MetaTrader 5 tab -->
+      <div class="settings-panel" id="stab-mt5">
+        <div class="settings-section-label">Terminal Paths</div>
+        <div class="settings-grid full">
+          <div class="settings-field">
+            <label>Terminal Executable</label>
+            <input type="text" class="settings-input mono" id="s-mt5-exe" placeholder="C:/Program Files/MetaTrader 5/terminal64.exe">
+            <div class="settings-hint">Full path to terminal64.exe</div>
+          </div>
+          <div class="settings-field" style="margin-top:0.5rem;">
+            <label>AppData Path</label>
+            <input type="text" class="settings-input mono" id="s-mt5-appdata" placeholder="C:/Users/.../AppData/Roaming/MetaQuotes/Terminal/...">
+          </div>
+          <div class="settings-field" style="margin-top:0.5rem;">
+            <label>MQL5 Files Path</label>
+            <input type="text" class="settings-input mono" id="s-mt5-mql5" placeholder="C:/Users/.../MQL5/Files">
+          </div>
+        </div>
+        <div class="settings-section-label">Tester Settings</div>
+        <div class="settings-grid">
+          <div class="settings-field">
+            <label>Tester Timeout (seconds)</label>
+            <input type="number" class="settings-input" id="s-mt5-timeout" min="30" max="600" step="10">
+          </div>
+          <div class="settings-field">
+            <label>Tester Model</label>
+            <select class="settings-select" id="s-mt5-model">
+              <option value="1">1 — Every tick</option>
+              <option value="2">2 — Every tick based on real ticks</option>
+              <option value="3">3 — OHLC (M1)</option>
+              <option value="4">4 — Open prices only</option>
+              <option value="5">5 — Math calculations</option>
+            </select>
+            <div class="settings-hint">Strategy Tester modeling method</div>
+          </div>
+        </div>
+      </div>
+
+      <!-- Broker tab -->
+      <div class="settings-panel" id="stab-broker">
+        <div class="settings-section-label">Broker Configuration</div>
+        <div class="settings-grid">
+          <div class="settings-field">
+            <label>Timezone Offset (hours)</label>
+            <input type="number" class="settings-input" id="s-broker-tz" min="-12" max="14" step="0.5">
+            <div class="settings-hint">GMT offset, e.g. 3 for EET (Eastern European Time)</div>
+          </div>
+          <div class="settings-field">
+            <label>Account Deposit ($)</label>
+            <input type="number" class="settings-input" id="s-broker-deposit" min="100" step="100">
+          </div>
+          <div class="settings-field">
+            <label>Leverage (1:X)</label>
+            <input type="number" class="settings-input" id="s-broker-leverage" min="1" max="2000" step="1">
+          </div>
+        </div>
+      </div>
+
+      <!-- Thresholds tab -->
+      <div class="settings-panel" id="stab-thresholds">
+        <div class="settings-section-label">Quality Filters</div>
+        <div class="settings-grid">
+          <div class="settings-field">
+            <label>Min Trades</label>
+            <input type="number" class="settings-input" id="s-thr-trades" min="1" step="1">
+            <div class="settings-hint">Minimum trades per backtest to pass</div>
+          </div>
+          <div class="settings-field">
+            <label>Min Profit Factor</label>
+            <input type="number" class="settings-input" id="s-thr-pf" min="0" max="10" step="0.05">
+          </div>
+          <div class="settings-field">
+            <label>Min Calmar Ratio</label>
+            <input type="number" class="settings-input" id="s-thr-calmar" min="0" max="10" step="0.05">
+          </div>
+          <div class="settings-field">
+            <label>Max OOS Degradation</label>
+            <input type="number" class="settings-input" id="s-thr-oos" min="0" max="1" step="0.01">
+            <div class="settings-hint">Max allowed out-of-sample score drop (0–1)</div>
+          </div>
+          <div class="settings-field">
+            <label>Sensitivity Tolerance</label>
+            <input type="number" class="settings-input" id="s-thr-sens" min="0" max="1" step="0.01">
+            <div class="settings-hint">Allowed parameter sensitivity variance (0–1)</div>
+          </div>
+        </div>
+      </div>
+
+    </div><!-- /.settings-body -->
+
+    <div class="settings-footer">
+      <span class="settings-save-msg" id="settings-save-msg" style="opacity:0;"></span>
+      <button class="settings-btn cancel" onclick="closeSettings()">Cancel</button>
+      <button class="settings-btn save" id="settings-save-btn" onclick="saveSettings()">Save Settings</button>
+    </div>
+
+  </div>
+</div>
+
+<!-- ══════════════════════════════════════
+     RUN DETAIL MODAL
+══════════════════════════════════════ -->
+<div class="run-detail-overlay" id="run-detail-overlay" style="display:none;" onclick="if(event.target===this)closeRunDetail()">
+  <div class="run-detail-card">
+
+    <div class="run-detail-header">
+      <div>
+        <div class="run-detail-title" id="rd-run-id">Run Details</div>
+        <div class="run-detail-sub" id="rd-meta"></div>
+      </div>
+      <button class="settings-close-btn" onclick="closeRunDetail()">✕</button>
+    </div>
+
+    <div class="run-detail-body">
+      <div class="rd-metrics-grid" id="rd-metrics"></div>
+
+      <div class="rd-section-title">Parameters</div>
+      <div class="rd-params-wrap">
+        <table class="params-table" style="width:100%">
+          <thead><tr><th>Parameter</th><th>Value</th></tr></thead>
+          <tbody id="rd-params-tbody">
+            <tr><td colspan="2" class="empty-state">Loading...</td></tr>
+          </tbody>
+        </table>
+      </div>
+
+      <div id="rd-ai-section" style="display:none;">
+        <div class="rd-section-title">AI Reasoning</div>
+        <div id="rd-ai-content"></div>
+      </div>
+    </div>
+
+    <div class="run-detail-footer" id="rd-footer">
+      <button class="verdict-btn ghost" onclick="closeRunDetail()">Close</button>
+    </div>
+
+  </div>
+</div>
+
+<!-- ══════════════════════════════════════
+     VERDICT OVERLAY
+══════════════════════════════════════ -->
+<div class="verdict-overlay" id="verdict-overlay" style="display:none;">
+  <div class="verdict-card" id="verdict-card">
+    <div class="verdict-header-row">
+      <div class="verdict-icon-big" id="verdict-icon">✅</div>
+      <div>
+        <div class="verdict-title" id="verdict-title">RECOMMENDED</div>
+        <div class="verdict-subtitle" id="verdict-subtitle">Optimization complete.</div>
+      </div>
+    </div>
+    <div class="verdict-metrics-row" id="verdict-metrics"></div>
+    <div class="verdict-actions-row" id="verdict-actions"></div>
+  </div>
+</div>
+
+<!-- ══════════════════════════════════════
+     SCRIPTS
+══════════════════════════════════════ -->
+<script src="https://cdn.socket.io/4.7.5/socket.io.min.js"></script>
+<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.4/dist/chart.umd.min.js"></script>
+<script src="/static/js/dashboard.js"></script>
+
 </body>
 </html>
diff --git a/ui/templates/landing.html b/ui/templates/landing.html
index 03fd693..d9a7255 100644
--- a/ui/templates/landing.html
+++ b/ui/templates/landing.html
@@ -1,267 +1,456 @@
 <!DOCTYPE html>
 <html lang="en">
 <head>
-<meta charset="UTF-8">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-<title>MT5 Smart Optimizer</title>
-<link rel="preconnect" href="https://fonts.googleapis.com">
-<link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800;900&display=swap" rel="stylesheet">
-<style>
-  *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1.0">
+  <title>APEX — AI-Powered EA Optimizer</title>
+  <link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800;900&display=swap" rel="stylesheet">
+  <style>
+    :root {
+      --bg: #080d1a;
+      --accent: #4f46e5;
+      --accent2: #7c6dfa;
+      --teal: #00d4aa;
+      --text: #e2e8f0;
+      --muted: #64748b;
+    }
 
-  :root {
-    --bg:      #07090f;
-    --bg2:     #0d1117;
-    --bg3:     #141b27;
-    --border:  rgba(255,255,255,0.07);
-    --accent:  #00d4aa;
-    --accent2: #7c6dfa;
-    --warn:    #f59e0b;
-    --text:    #e2e8f0;
-    --muted:   #64748b;
-    --glow:    0 0 40px rgba(0,212,170,0.15);
-  }
+    * { box-sizing: border-box; margin: 0; padding: 0; }
 
-  html, body { height: 100%; }
+    body {
+      font-family: 'Inter', sans-serif;
+      background: var(--bg);
+      color: var(--text);
+      min-height: 100vh;
+      overflow-x: hidden;
+    }
 
-  body {
-    font-family: 'Inter', sans-serif;
-    background: var(--bg);
-    color: var(--text);
-    display: grid;
-    place-items: center;
-    min-height: 100vh;
-    overflow: hidden;
-  }
+    /* Grid overlay */
+    body::before {
+      content: '';
+      position: fixed; inset: 0;
+      background-image:
+        linear-gradient(rgba(0,212,170,0.03) 1px, transparent 1px),
+        linear-gradient(90deg, rgba(0,212,170,0.03) 1px, transparent 1px);
+      background-size: 50px 50px;
+      pointer-events: none;
+      z-index: 0;
+    }
 
-  /* Animated background grid */
-  body::before {
-    content: '';
-    position: fixed; inset: 0;
-    background-image:
-      linear-gradient(rgba(0,212,170,0.03) 1px, transparent 1px),
-      linear-gradient(90deg, rgba(0,212,170,0.03) 1px, transparent 1px);
-    background-size: 60px 60px;
-    animation: gridScroll 20s linear infinite;
-    pointer-events: none;
-    z-index: 0;
-  }
-  @keyframes gridScroll { to { background-position: 60px 60px; } }
+    /* Glow orb */
+    body::after {
+      content: '';
+      position: fixed;
+      top: 20%;
+      left: 10%;
+      width: 600px;
+      height: 600px;
+      background: radial-gradient(circle, rgba(79,70,229,0.08) 0%, transparent 70%);
+      pointer-events: none;
+      z-index: 0;
+    }
 
-  /* Glowing orbs */
-  .orb {
-    position: fixed;
-    border-radius: 50%;
-    filter: blur(120px);
-    opacity: 0.12;
-    pointer-events: none;
-    z-index: 0;
-    animation: orb-float 8s ease-in-out infinite;
-  }
-  .orb-1 { width: 600px; height: 600px; background: var(--accent); top: -200px; left: -100px; animation-delay: 0s; }
-  .orb-2 { width: 500px; height: 500px; background: var(--accent2); bottom: -200px; right: -100px; animation-delay: 4s; }
-  @keyframes orb-float { 0%,100%{transform:translateY(0)} 50%{transform:translateY(-30px)} }
+    .page {
+      position: relative;
+      z-index: 1;
+      max-width: 1200px;
+      margin: 0 auto;
+      padding: 2rem;
+    }
 
-  .landing {
-    position: relative;
-    z-index: 1;
-    text-align: center;
-    max-width: 700px;
-    padding: 2rem;
-    animation: fadeUp 0.8s ease both;
-  }
-  @keyframes fadeUp { from{opacity:0;transform:translateY(30px)} to{opacity:1;transform:translateY(0)} }
+    /* Navbar */
+    .navbar {
+      display: flex;
+      align-items: center;
+      justify-content: space-between;
+      padding: 1.5rem 0;
+      margin-bottom: 4rem;
+    }
 
-  .logo {
-    display: inline-flex;
-    align-items: center;
-    gap: 0.75rem;
-    margin-bottom: 2.5rem;
-  }
-  .logo-icon {
-    width: 52px; height: 52px;
-    background: linear-gradient(135deg, var(--accent), var(--accent2));
-    border-radius: 14px;
-    display: grid; place-items: center;
-    font-size: 1.6rem;
-    box-shadow: var(--glow);
-  }
-  .logo-name {
-    font-size: 1.4rem;
-    font-weight: 700;
-    letter-spacing: -0.02em;
-    color: white;
-  }
-  .logo-sub { font-size: 0.75rem; color: var(--muted); margin-top: 2px; }
+    .nav-logo {
+      display: flex;
+      align-items: center;
+      gap: 0.75rem;
+    }
 
-  h1 {
-    font-size: clamp(2.2rem, 5vw, 3.5rem);
-    font-weight: 900;
-    letter-spacing: -0.04em;
-    line-height: 1.1;
-    margin-bottom: 1.25rem;
-    background: linear-gradient(135deg, #ffffff 0%, var(--accent) 60%, var(--accent2) 100%);
-    -webkit-background-clip: text;
-    -webkit-text-fill-color: transparent;
-    background-clip: text;
-  }
+    .nav-logo-text {
+      font-size: 1.25rem;
+      font-weight: 800;
+      letter-spacing: 0.05em;
+      background: linear-gradient(135deg, #fff 0%, #94a3b8 100%);
+      -webkit-background-clip: text;
+      -webkit-text-fill-color: transparent;
+    }
 
-  .subtitle {
-    font-size: 1.1rem;
-    color: var(--muted);
-    line-height: 1.7;
-    margin-bottom: 3rem;
-    font-weight: 400;
-  }
+    .status-pill {
+      display: flex;
+      align-items: center;
+      gap: 0.5rem;
+      padding: 0.4rem 1rem;
+      background: rgba(255,255,255,0.05);
+      border: 1px solid rgba(255,255,255,0.1);
+      border-radius: 999px;
+      font-size: 0.8rem;
+      color: var(--muted);
+    }
 
-  .actions {
-    display: flex;
-    gap: 1rem;
-    justify-content: center;
-    flex-wrap: wrap;
-  }
+    .status-dot {
+      width: 8px; height: 8px;
+      border-radius: 50%;
+      background: var(--muted);
+      flex-shrink: 0;
+    }
+    .status-dot.running {
+      background: var(--teal);
+      box-shadow: 0 0 8px var(--teal);
+      animation: pulse 1.5s infinite;
+    }
+    .status-dot.idle { background: #475569; }
+    @keyframes pulse { 0%,100%{opacity:1} 50%{opacity:0.5} }
 
-  .btn {
-    display: inline-flex;
-    align-items: center;
-    gap: 0.6rem;
-    padding: 0.9rem 2rem;
-    border-radius: 12px;
-    font-size: 1rem;
-    font-weight: 600;
-    text-decoration: none;
-    transition: all 0.2s ease;
-    cursor: pointer;
-    border: none;
-    font-family: inherit;
-  }
+    /* Hero */
+    .hero {
+      display: grid;
+      grid-template-columns: 1fr 1fr;
+      gap: 4rem;
+      align-items: center;
+      min-height: 70vh;
+    }
 
-  .btn-primary {
-    background: linear-gradient(135deg, var(--accent), #00b890);
-    color: #051a14;
-    box-shadow: 0 4px 24px rgba(0,212,170,0.35);
-  }
-  .btn-primary:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 8px 36px rgba(0,212,170,0.5);
-  }
+    .hero-badge {
+      display: inline-flex;
+      align-items: center;
+      gap: 0.5rem;
+      padding: 0.35rem 0.9rem;
+      background: rgba(79,70,229,0.15);
+      border: 1px solid rgba(79,70,229,0.3);
+      border-radius: 999px;
+      font-size: 0.72rem;
+      font-weight: 600;
+      color: var(--accent2);
+      letter-spacing: 0.08em;
+      text-transform: uppercase;
+      margin-bottom: 1.5rem;
+    }
 
-  .btn-secondary {
-    background: var(--bg3);
-    color: var(--text);
-    border: 1px solid var(--border);
-  }
-  .btn-secondary:hover {
-    background: #1e2a3f;
-    border-color: rgba(255,255,255,0.15);
-    transform: translateY(-2px);
-  }
+    .hero-logo-row {
+      display: flex;
+      align-items: center;
+      gap: 1.25rem;
+      margin-bottom: 0.5rem;
+    }
 
-  .stats {
-    display: flex;
-    gap: 2rem;
-    justify-content: center;
-    margin-top: 3.5rem;
-    padding-top: 2.5rem;
-    border-top: 1px solid var(--border);
-  }
-  .stat { text-align: center; }
-  .stat-val {
-    font-size: 1.6rem;
-    font-weight: 800;
-    color: var(--accent);
-    letter-spacing: -0.03em;
-  }
-  .stat-label { font-size: 0.75rem; color: var(--muted); margin-top: 0.2rem; text-transform: uppercase; letter-spacing: 0.08em; }
+    .hero-title {
+      font-size: 5rem;
+      font-weight: 900;
+      letter-spacing: -0.04em;
+      line-height: 1;
+      background: linear-gradient(135deg, #ffffff 0%, #c7d2fe 50%, #00d4aa 100%);
+      -webkit-background-clip: text;
+      -webkit-text-fill-color: transparent;
+    }
 
-  .status-pill {
-    display: inline-flex;
-    align-items: center;
-    gap: 0.4rem;
-    padding: 0.3rem 0.8rem;
-    background: rgba(0,212,170,0.1);
-    border: 1px solid rgba(0,212,170,0.2);
-    border-radius: 999px;
-    font-size: 0.78rem;
-    color: var(--accent);
-    margin-bottom: 2rem;
-  }
-  .pulse {
-    width: 7px; height: 7px;
-    background: var(--accent);
-    border-radius: 50%;
-    animation: pulse 2s ease infinite;
-  }
-  @keyframes pulse { 0%,100%{opacity:1;transform:scale(1)} 50%{opacity:0.5;transform:scale(0.8)} }
-</style>
+    .hero-subtitle-row {
+      font-size: 0.85rem;
+      font-weight: 700;
+      letter-spacing: 0.2em;
+      text-transform: uppercase;
+      color: var(--muted);
+      margin-bottom: 1.5rem;
+    }
+
+    .hero-tagline {
+      font-size: 1.5rem;
+      font-weight: 300;
+      color: #94a3b8;
+      margin-bottom: 2.5rem;
+      line-height: 1.5;
+    }
+
+    .hero-tagline strong {
+      color: var(--teal);
+      font-weight: 600;
+    }
+
+    .hero-ctas {
+      display: flex;
+      gap: 1rem;
+      margin-bottom: 3rem;
+      flex-wrap: wrap;
+    }
+
+    .btn-primary {
+      display: inline-flex; align-items: center; gap: 0.5rem;
+      padding: 0.9rem 2rem;
+      background: linear-gradient(135deg, var(--accent), var(--accent2));
+      color: white; border: none; border-radius: 10px;
+      font-size: 0.95rem; font-weight: 700; cursor: pointer;
+      text-decoration: none; font-family: inherit;
+      box-shadow: 0 4px 24px rgba(79,70,229,0.4);
+      transition: all 0.2s;
+    }
+    .btn-primary:hover { transform: translateY(-2px); box-shadow: 0 8px 36px rgba(79,70,229,0.5); }
+
+    .btn-secondary {
+      display: inline-flex; align-items: center; gap: 0.5rem;
+      padding: 0.9rem 1.75rem;
+      background: rgba(255,255,255,0.06);
+      border: 1px solid rgba(255,255,255,0.12);
+      color: var(--text); border-radius: 10px;
+      font-size: 0.95rem; font-weight: 600;
+      text-decoration: none; font-family: inherit;
+      transition: all 0.2s;
+    }
+    .btn-secondary:hover { background: rgba(255,255,255,0.1); }
+
+    .hero-stats {
+      display: flex;
+      gap: 2rem;
+      flex-wrap: wrap;
+    }
+
+    .hero-stat { display: flex; flex-direction: column; }
+    .hero-stat-val {
+      font-size: 1.5rem; font-weight: 800;
+      background: linear-gradient(135deg, var(--teal), var(--accent2));
+      -webkit-background-clip: text; -webkit-text-fill-color: transparent;
+    }
+    .hero-stat-lbl {
+      font-size: 0.72rem; color: var(--muted); margin-top: 0.1rem;
+    }
+
+    /* Features panel */
+    .features-panel {
+      background: rgba(15,22,41,0.8);
+      border: 1px solid rgba(255,255,255,0.1);
+      border-radius: 20px;
+      padding: 2rem;
+      backdrop-filter: blur(10px);
+      position: relative;
+      overflow: hidden;
+    }
+
+    .features-panel::before {
+      content: 'APEX';
+      position: absolute;
+      top: 50%;
+      left: 50%;
+      transform: translate(-50%, -50%);
+      font-size: 4rem;
+      font-weight: 900;
+      letter-spacing: 0.1em;
+      background: linear-gradient(135deg, #4f46e5, #00d4aa);
+      -webkit-background-clip: text; -webkit-text-fill-color: transparent;
+      opacity: 0.15;
+      pointer-events: none;
+      white-space: nowrap;
+    }
+
+    .features-panel-title {
+      font-size: 0.75rem; font-weight: 700;
+      text-transform: uppercase; letter-spacing: 0.15em;
+      color: var(--muted); margin-bottom: 1.5rem;
+      text-align: center;
+    }
+
+    .features-list { display: flex; flex-direction: column; gap: 1.25rem; }
+
+    .feature-item { display: flex; align-items: flex-start; gap: 1rem; }
+
+    .feature-icon-wrap {
+      width: 40px; height: 40px;
+      border-radius: 10px;
+      display: flex; align-items: center; justify-content: center;
+      flex-shrink: 0;
+      font-size: 1.1rem;
+    }
+    .feature-icon-wrap.purple { background: rgba(79,70,229,0.2); border: 1px solid rgba(79,70,229,0.3); }
+    .feature-icon-wrap.teal   { background: rgba(0,212,170,0.15); border: 1px solid rgba(0,212,170,0.3); }
+    .feature-icon-wrap.blue   { background: rgba(59,130,246,0.15); border: 1px solid rgba(59,130,246,0.3); }
+    .feature-icon-wrap.green  { background: rgba(16,185,129,0.15); border: 1px solid rgba(16,185,129,0.3); }
+
+    .feature-name {
+      font-size: 0.72rem; font-weight: 700;
+      letter-spacing: 0.1em; text-transform: uppercase;
+      margin-bottom: 0.2rem;
+    }
+    .feature-name.purple { color: var(--accent2); }
+    .feature-name.teal   { color: var(--teal); }
+    .feature-name.blue   { color: #60a5fa; }
+    .feature-name.green  { color: #34d399; }
+
+    .feature-desc { font-size: 0.8rem; color: #94a3b8; line-height: 1.5; }
+
+    /* Footer */
+    .footer {
+      margin-top: 4rem;
+      padding-top: 2rem;
+      border-top: 1px solid rgba(255,255,255,0.06);
+      display: flex;
+      justify-content: space-between;
+      align-items: center;
+      color: var(--muted);
+      font-size: 0.8rem;
+    }
+
+    @media (max-width: 768px) {
+      .hero { grid-template-columns: 1fr; min-height: auto; }
+      .hero-title { font-size: 3rem; }
+      .features-panel { display: none; }
+      .hero-stats { gap: 1.25rem; }
+    }
+  </style>
 </head>
 <body>
-<div class="orb orb-1"></div>
-<div class="orb orb-2"></div>
+<div class="page">
 
-<div class="landing">
+  <!-- Navbar -->
+  <nav class="navbar">
+    <div class="nav-logo">
+      <svg width="32" height="32" viewBox="0 0 36 36" fill="none">
+        <polygon points="18,2 34,32 2,32" fill="url(#logoGradL)" opacity="0.15"/>
+        <polygon points="18,8 30,30 6,30" fill="url(#logoGradL)" opacity="0.3"/>
+        <path d="M18 6L22 14H14L18 6Z" fill="url(#logoGradL)"/>
+        <rect x="11" y="22" width="3" height="8" rx="1" fill="#00d4aa"/>
+        <rect x="16" y="18" width="3" height="12" rx="1" fill="#00d4aa" opacity="0.8"/>
+        <rect x="21" y="14" width="3" height="16" rx="1" fill="#00d4aa" opacity="0.6"/>
+        <defs>
+          <linearGradient id="logoGradL" x1="0" y1="0" x2="1" y2="1">
+            <stop offset="0%" stop-color="#4f46e5"/>
+            <stop offset="100%" stop-color="#00d4aa"/>
+          </linearGradient>
+        </defs>
+      </svg>
+      <span class="nav-logo-text">APEX</span>
+    </div>
+    <div class="status-pill" id="status-pill">
+      <div class="status-dot idle" id="status-dot"></div>
+      <span id="status-text">Ready</span>
+    </div>
+  </nav>
 
-  <div class="logo">
-    <div class="logo-icon">⚡</div>
-    <div>
-      <div class="logo-name">MT5 Smart Optimizer</div>
-      <div class="logo-sub">Autonomous EA Optimization Engine</div>
+  <!-- Hero -->
+  <div class="hero">
+    <div class="hero-left">
+      <div class="hero-badge">&#10022; Hackathon Edition 2026</div>
+
+      <div class="hero-logo-row">
+        <svg width="72" height="72" viewBox="0 0 72 72" fill="none">
+          <polygon points="36,4 68,64 4,64" fill="url(#heroGrad)" opacity="0.12"/>
+          <polygon points="36,16 60,60 12,60" fill="url(#heroGrad)" opacity="0.25"/>
+          <path d="M36 12L44 28H28L36 12Z" fill="url(#heroGrad)"/>
+          <path d="M33 20L36 13L39 20" stroke="#00d4aa" stroke-width="1.5" fill="none" stroke-linecap="round"/>
+          <rect x="22" y="44" width="6" height="16" rx="2" fill="#00d4aa" opacity="0.9"/>
+          <rect x="33" y="36" width="6" height="24" rx="2" fill="#00d4aa" opacity="0.7"/>
+          <rect x="44" y="28" width="6" height="32" rx="2" fill="#00d4aa" opacity="0.5"/>
+          <defs>
+            <linearGradient id="heroGrad" x1="0" y1="0" x2="1" y2="1">
+              <stop offset="0%" stop-color="#4f46e5"/>
+              <stop offset="100%" stop-color="#7c6dfa"/>
+            </linearGradient>
+          </defs>
+        </svg>
+      </div>
+
+      <div class="hero-title">APEX</div>
+      <div class="hero-subtitle-row">AI Powered EA Optimizer</div>
+
+      <div class="hero-tagline">
+        Optimize. <strong>Understand.</strong> Evolve.<br>
+        <span style="font-size:1rem">The first optimizer that tells you <em>why</em> &mdash; not just what.</span>
+      </div>
+
+      <div class="hero-ctas">
+        <a href="/setup" class="btn-primary">&#9889; Start Optimizing &rarr;</a>
+        <a href="/dashboard" class="btn-secondary">&#128202; Live Dashboard</a>
+        <a href="/reports" class="btn-secondary">&#128203; Reports</a>
+      </div>
+
+      <div class="hero-stats">
+        <div class="hero-stat">
+          <div class="hero-stat-val">3</div>
+          <div class="hero-stat-lbl">Phase Pipeline</div>
+        </div>
+        <div class="hero-stat">
+          <div class="hero-stat-val">AI</div>
+          <div class="hero-stat-lbl">Claude-Powered</div>
+        </div>
+        <div class="hero-stat">
+          <div class="hero-stat-val">IS/OOS</div>
+          <div class="hero-stat-lbl">Walk-Forward Validated</div>
+        </div>
+        <div class="hero-stat">
+          <div class="hero-stat-val">Any EA</div>
+          <div class="hero-stat-lbl">Works with any .set file</div>
+        </div>
+      </div>
+    </div>
+
+    <div class="hero-right">
+      <div class="features-panel">
+        <div class="features-panel-title">What makes APEX different</div>
+        <div class="features-list">
+
+          <div class="feature-item">
+            <div class="feature-icon-wrap purple">&#129504;</div>
+            <div>
+              <div class="feature-name purple">AI Reasoning</div>
+              <div class="feature-desc">Analyzes results, detects patterns and explains performance in plain language using Claude AI.</div>
+            </div>
+          </div>
+
+          <div class="feature-item">
+            <div class="feature-icon-wrap teal">&#127919;</div>
+            <div>
+              <div class="feature-name teal">Smart Optimization</div>
+              <div class="feature-desc">Finds the best parameters using 3-phase search: broad discovery &rarr; refinement &rarr; out-of-sample validation.</div>
+            </div>
+          </div>
+
+          <div class="feature-item">
+            <div class="feature-icon-wrap blue" style="font-size:0.85rem;font-weight:700;font-family:monospace;color:#60a5fa">&lt;/&gt;</div>
+            <div>
+              <div class="feature-name blue">Strategy Evolution</div>
+              <div class="feature-desc">Suggests improvements and helps evolve your trading systems based on behavioral pattern analysis.</div>
+            </div>
+          </div>
+
+          <div class="feature-item">
+            <div class="feature-icon-wrap green">&#128737;</div>
+            <div>
+              <div class="feature-name green">Robust &amp; Reliable</div>
+              <div class="feature-desc">Built-in validation (IS/OOS/WFV) and sensitivity testing to ensure real market reliability.</div>
+            </div>
+          </div>
+
+        </div>
+      </div>
     </div>
   </div>
 
-  <div class="status-pill" id="status-pill">
-    <div class="pulse"></div>
-    <span id="status-text">Ready</span>
-  </div>
-
-  <h1>Find the Best Settings<br>for Any MT5 EA</h1>
-
-  <p class="subtitle">
-    The Smart Optimizer tests dozens of configurations across your full parameter space,
-    validates the winner on unseen data, and delivers a ready-to-use .set file — in under an hour.
-  </p>
-
-  <div class="actions">
-    <a href="/setup" class="btn btn-primary">
-      ⚡ New Optimization
-    </a>
-    <a href="/dashboard" class="btn btn-secondary" id="dashboard-btn">
-      📊 Live Dashboard
-    </a>
-    <a href="/reports" class="btn btn-secondary">
-      📁 View Reports
-    </a>
-  </div>
-
-  <div class="stats">
-    <div class="stat">
-      <div class="stat-val">3</div>
-      <div class="stat-label">Phases</div>
-    </div>
-    <div class="stat">
-      <div class="stat-val" id="stat-runs">20–50</div>
-      <div class="stat-label">Config Tests</div>
-    </div>
-    <div class="stat">
-      <div class="stat-val">&lt;1hr</div>
-      <div class="stat-label">Typical Time</div>
-    </div>
-    <div class="stat">
-      <div class="stat-val">OOS</div>
-      <div class="stat-label">Validated</div>
-    </div>
-  </div>
+  <footer class="footer">
+    <span>APEX &mdash; AI-Powered EA Optimizer</span>
+    <span>Powered by Claude AI + MetaTrader 5</span>
+  </footer>
 </div>
 
 <script>
-  // Check if optimizer is running
-  fetch('/api/status').then(r => r.json()).then(s => {
-    if (s.state === 'running') {
-      document.getElementById('status-text').textContent = `Running — ${s.phase} (${s.run_count}/${s.total_runs})`;
-      document.getElementById('dashboard-btn').style.background = 'linear-gradient(135deg,#7c6dfa,#5b4fe8)';
-      document.getElementById('dashboard-btn').style.color = 'white';
-    }
-  }).catch(() => {});
+  // Fetch optimizer status and update the live pill
+  fetch('/api/status')
+    .then(function(r) { return r.json(); })
+    .then(function(s) {
+      var dot = document.getElementById('status-dot');
+      var txt = document.getElementById('status-text');
+      if (s.state === 'running') {
+        dot.className = 'status-dot running';
+        txt.textContent = 'Running: ' + (s.phase || '') + ' (' + (s.run_count || 0) + ' runs)';
+      } else if (s.verdict) {
+        dot.className = 'status-dot';
+        dot.style.background = '#10b981';
+        txt.textContent = 'Last: ' + s.verdict;
+      }
+    })
+    .catch(function() {});
 </script>
 </body>
 </html>
diff --git a/ui/templates/setup.html b/ui/templates/setup.html
index ea864a1..8c1480a 100644
--- a/ui/templates/setup.html
+++ b/ui/templates/setup.html
@@ -370,6 +370,161 @@
       </div>
     </div>
 
+    <!-- Add New EA -->
+    <div style="margin-top:0.5rem;display:flex;gap:0.75rem;align-items:center;flex-wrap:wrap">
+      <button type="button" onclick="showAddEAModal()"
+        style="background:none;border:1px dashed rgba(79,70,229,0.4);color:#7c6dfa;padding:0.4rem 1rem;border-radius:8px;font-size:0.8rem;cursor:pointer;font-family:inherit;transition:all 0.2s"
+        onmouseover="this.style.borderColor='#7c6dfa'" onmouseout="this.style.borderColor='rgba(79,70,229,0.4)'">
+        + Register New EA
+      </button>
+      <button type="button" id="scan-btn" onclick="scanForEAs()"
+        style="background:none;border:1px dashed rgba(0,212,170,0.35);color:#00d4aa;padding:0.4rem 1rem;border-radius:8px;font-size:0.8rem;cursor:pointer;font-family:inherit;transition:all 0.2s;display:flex;align-items:center;gap:0.4rem"
+        onmouseover="this.style.borderColor='#00d4aa'" onmouseout="this.style.borderColor='rgba(0,212,170,0.35)'">
+        <svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2.5"><circle cx="11" cy="11" r="8"/><path d="M21 21l-4.35-4.35"/></svg>
+        Scan for EAs
+      </button>
+      <span id="scan-status" style="font-size:0.78rem;color:#64748b"></span>
+    </div>
+
+    <!-- Add EA Modal -->
+    <div id="add-ea-modal" style="display:none;position:fixed;inset:0;background:rgba(0,0,0,0.75);z-index:50;align-items:center;justify-content:center;backdrop-filter:blur(6px)">
+      <div style="background:#0d1117;border:1px solid rgba(255,255,255,0.1);border-radius:16px;padding:2rem;width:540px;max-width:95vw;max-height:90vh;overflow-y:auto">
+        <div style="display:flex;justify-content:space-between;align-items:center;margin-bottom:1.5rem">
+          <div>
+            <h3 style="font-size:1.05rem;font-weight:700;color:#e2e8f0">Register New EA</h3>
+            <p style="font-size:0.78rem;color:#64748b;margin-top:0.2rem">Pick a detected EA or enter paths manually</p>
+          </div>
+          <button onclick="hideAddEAModal()" style="background:none;border:none;color:#64748b;cursor:pointer;font-size:1.4rem;line-height:1">&#10005;</button>
+        </div>
+
+        <!-- Detected EAs picker (shown after scan) -->
+        <div id="detected-section" style="display:none;margin-bottom:1.25rem">
+          <div style="font-size:0.78rem;font-weight:600;text-transform:uppercase;letter-spacing:0.08em;color:#00d4aa;margin-bottom:0.6rem">
+            Detected EAs — click to auto-fill
+          </div>
+          <div id="detected-list" style="display:flex;flex-direction:column;gap:0.4rem;max-height:180px;overflow-y:auto;padding-right:4px"></div>
+          <div style="margin:1rem 0;border-top:1px solid rgba(255,255,255,0.06)"></div>
+        </div>
+
+        <div style="display:flex;flex-direction:column;gap:1rem">
+          <div class="field">
+            <label>EA Display Name</label>
+            <input type="text" id="new-ea-name" placeholder="e.g. MyEA_v2">
+          </div>
+          <div class="field">
+            <label>EA File Name (without .ex5)</label>
+            <input type="text" id="new-ea-file" placeholder="e.g. MyEA_v2">
+          </div>
+          <div class="field">
+            <label style="display:flex;align-items:center;justify-content:space-between">
+              <span>.set Template Path</span>
+              <span id="set-match-badge" style="display:none;font-size:0.7rem;background:rgba(0,212,170,0.15);color:#00d4aa;padding:2px 8px;border-radius:999px;font-weight:600">✓ auto-matched</span>
+            </label>
+            <input type="text" id="new-ea-set" placeholder="C:\MT5 Set files\MyEA.set">
+            <!-- Set file picker (shown after scan) -->
+            <select id="set-picker" style="display:none;margin-top:0.4rem;font-size:0.82rem" onchange="onSetPick()">
+              <option value="">— pick from detected .set files —</option>
+            </select>
+          </div>
+          <div class="grid-2">
+            <div class="field">
+              <label>Symbol</label>
+              <select id="new-ea-symbol">
+                <option value="XAUUSD">XAUUSD (Gold)</option>
+                <option value="EURUSD">EURUSD</option>
+                <option value="GBPUSD">GBPUSD</option>
+                <option value="USDJPY">USDJPY</option>
+                <option value="USDCAD">USDCAD</option>
+                <option value="AUDUSD">AUDUSD</option>
+                <option value="BTCUSD">BTCUSD</option>
+                <option value="NASDAQ">NASDAQ</option>
+                <option value="US30">US30</option>
+                <option value="DE40">DE40</option>
+              </select>
+            </div>
+            <div class="field">
+              <label>Timeframe</label>
+              <select id="new-ea-tf">
+                <option value="M5">M5</option>
+                <option value="M15">M15</option>
+                <option value="M30">M30</option>
+                <option value="H1" selected>H1</option>
+                <option value="H4">H4</option>
+                <option value="D1">D1</option>
+              </select>
+            </div>
+          </div>
+        </div>
+
+        <div style="display:flex;gap:0.75rem;margin-top:1.5rem;justify-content:flex-end">
+          <button type="button" onclick="hideAddEAModal()"
+            style="padding:0.6rem 1.25rem;background:rgba(255,255,255,0.06);border:1px solid rgba(255,255,255,0.1);color:#e2e8f0;border-radius:8px;cursor:pointer;font-family:inherit">
+            Cancel
+          </button>
+          <button type="button" onclick="registerNewEA()"
+            style="padding:0.6rem 1.5rem;background:linear-gradient(135deg,#4f46e5,#7c6dfa);color:white;border:none;border-radius:8px;font-weight:700;cursor:pointer;font-family:inherit">
+            Register EA
+          </button>
+        </div>
+      </div>
+    </div>
+
+    <!-- Autonomous AI Loop -->
+    <div style="border:1px solid rgba(0,212,170,0.25);border-radius:12px;padding:1.25rem 1.5rem;background:rgba(0,212,170,0.04);margin-top:0.5rem">
+      <div style="display:flex;align-items:center;justify-content:space-between;margin-bottom:0.75rem">
+        <div>
+          <div style="display:flex;align-items:center;gap:0.6rem">
+            <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="#00d4aa" stroke-width="2"><polygon points="13 2 3 14 12 14 11 22 21 10 12 10 13 2"/></svg>
+            <span style="font-size:0.88rem;font-weight:700;color:#e2e8f0">Autonomous AI Loop</span>
+            <span style="font-size:0.62rem;background:rgba(0,212,170,0.18);color:#00d4aa;padding:2px 7px;border-radius:999px;font-weight:700;letter-spacing:0.05em">NEW</span>
+          </div>
+          <div style="font-size:0.72rem;color:#64748b;margin-top:0.25rem">
+            AI analyzes results and evolves parameters each iteration until targets are met
+          </div>
+        </div>
+        <!-- Toggle -->
+        <button type="button" class="settings-toggle" id="autonomous-toggle"
+          onclick="toggleAutonomous(this)"
+          style="width:44px;height:24px;background:rgba(255,255,255,0.12);border-radius:999px;border:none;cursor:pointer;position:relative;transition:background 0.2s;flex-shrink:0">
+        </button>
+      </div>
+
+      <!-- Expanded controls (hidden when off) -->
+      <div id="autonomous-controls" style="display:none">
+        <div style="display:grid;grid-template-columns:1fr 1fr 1fr;gap:0.75rem;margin-bottom:0.75rem">
+          <div class="field" style="margin:0">
+            <label>Max Iterations</label>
+            <input type="number" name="autonomous_max_iterations" id="ai-max-iter"
+              value="10" min="3" max="50" step="1" class="input" style="margin-top:0.3rem">
+          </div>
+          <div class="field" style="margin:0">
+            <label>Target Profit Factor</label>
+            <input type="number" name="target_profit_factor" id="ai-target-pf"
+              value="1.5" min="1.0" max="5.0" step="0.1" class="input" style="margin-top:0.3rem">
+          </div>
+          <div class="field" style="margin:0">
+            <label>Target Max Drawdown %</label>
+            <input type="number" name="target_max_drawdown_pct" id="ai-target-dd"
+              value="20" min="5" max="50" step="1" class="input" style="margin-top:0.3rem">
+          </div>
+        </div>
+        <div style="display:grid;grid-template-columns:1fr 2fr;gap:0.75rem">
+          <div class="field" style="margin:0">
+            <label>Target Min Calmar</label>
+            <input type="number" name="target_min_calmar" id="ai-target-calmar"
+              value="0.5" min="0.1" max="5.0" step="0.05" class="input" style="margin-top:0.3rem">
+          </div>
+          <div style="background:rgba(255,255,255,0.03);border:1px solid rgba(255,255,255,0.07);border-radius:8px;padding:0.6rem 0.9rem;font-size:0.72rem;color:#64748b;line-height:1.55">
+            Loop stops early when <strong style="color:#e2e8f0">ALL</strong> targets are met simultaneously.
+            Requires an Anthropic API key configured in Settings.
+          </div>
+        </div>
+      </div>
+
+      <!-- Hidden inputs for form submission -->
+      <input type="hidden" name="autonomous_mode" id="autonomous-mode-val" value="false">
+    </div>
+
     <!-- Submit -->
     <div class="submit-row">
       <button type="submit" class="btn-start" id="start-btn">
@@ -419,13 +574,242 @@
     body.classList.toggle('open');
   }
 
+  let scannedData = null;  // cache from /api/ea/scan
+
+  function showAddEAModal() {
+    document.getElementById('add-ea-modal').style.display = 'flex';
+    // If we already scanned, populate the detected section
+    if (scannedData) populateDetected(scannedData);
+  }
+
+  function hideAddEAModal() {
+    document.getElementById('add-ea-modal').style.display = 'none';
+  }
+
+  async function scanForEAs() {
+    const btn = document.getElementById('scan-btn');
+    const status = document.getElementById('scan-status');
+    btn.style.opacity = '0.5';
+    btn.style.pointerEvents = 'none';
+    status.textContent = 'Scanning...';
+    try {
+      const resp = await fetch('/api/ea/scan');
+      const data = await resp.json();
+      scannedData = data;
+      const count = data.ex5.length;
+      const setCount = data.set.length;
+      status.style.color = '#00d4aa';
+      status.textContent = `Found ${count} EA${count !== 1 ? 's' : ''} · ${setCount} .set file${setCount !== 1 ? 's' : ''}`;
+      showAddEAModal();
+    } catch(e) {
+      status.style.color = '#ef4444';
+      status.textContent = 'Scan failed: ' + e.message;
+    } finally {
+      btn.style.opacity = '';
+      btn.style.pointerEvents = '';
+    }
+  }
+
+  function populateDetected(data) {
+    const section = document.getElementById('detected-section');
+    const list    = document.getElementById('detected-list');
+    const picker  = document.getElementById('set-picker');
+
+    if (!data.ex5.length && !data.set.length) return;
+
+    // Build EA pill list
+    list.innerHTML = '';
+    data.ex5.forEach(ea => {
+      const pill = document.createElement('button');
+      pill.type = 'button';
+      pill.style.cssText = 'display:flex;align-items:center;justify-content:space-between;padding:0.55rem 0.85rem;background:rgba(255,255,255,0.04);border:1px solid rgba(255,255,255,0.08);border-radius:9px;cursor:pointer;font-family:inherit;width:100%;text-align:left;transition:all 0.15s';
+      pill.onmouseover = () => { pill.style.background='rgba(124,109,250,0.12)'; pill.style.borderColor='rgba(124,109,250,0.4)'; };
+      pill.onmouseout  = () => { pill.style.background='rgba(255,255,255,0.04)'; pill.style.borderColor='rgba(255,255,255,0.08)'; };
+      pill.innerHTML = `
+        <span style="font-size:0.85rem;font-weight:600;color:#e2e8f0">${ea.name}</span>
+        ${ea.suggested_set
+          ? '<span style="font-size:0.7rem;background:rgba(0,212,170,0.15);color:#00d4aa;padding:2px 8px;border-radius:999px;font-weight:600">.set matched</span>'
+          : '<span style="font-size:0.7rem;color:#64748b">no .set matched</span>'
+        }
+      `;
+      pill.onclick = () => autoFillFromEA(ea);
+      list.appendChild(pill);
+    });
+
+    // Build .set picker
+    picker.innerHTML = '<option value="">— pick from detected .set files —</option>';
+    data.set.forEach(s => {
+      const opt = new Option(s.filename, s.path);
+      picker.add(opt);
+    });
+    picker.style.display = data.set.length ? 'block' : 'none';
+
+    section.style.display = 'block';
+  }
+
+  function autoFillFromEA(ea) {
+    document.getElementById('new-ea-name').value = ea.name;
+    document.getElementById('new-ea-file').value = ea.name;
+    if (ea.suggested_set) {
+      document.getElementById('new-ea-set').value = ea.suggested_set;
+      document.getElementById('set-match-badge').style.display = 'inline';
+    } else {
+      document.getElementById('new-ea-set').value = '';
+      document.getElementById('set-match-badge').style.display = 'none';
+    }
+    // Scroll to bottom of modal to show form fields
+    document.getElementById('add-ea-modal').querySelector('div').scrollTop = 999;
+  }
+
+  function onSetPick() {
+    const val = document.getElementById('set-picker').value;
+    if (val) {
+      document.getElementById('new-ea-set').value = val;
+      document.getElementById('set-match-badge').style.display = 'inline';
+    }
+  }
+
+  async function registerNewEA() {
+    const name = document.getElementById('new-ea-name').value.trim();
+    const file = document.getElementById('new-ea-file').value.trim();
+    const set  = document.getElementById('new-ea-set').value.trim();
+    const symbol    = document.getElementById('new-ea-symbol').value;
+    const timeframe = document.getElementById('new-ea-tf').value;
+
+    if (!name || !set) {
+      alert('EA Name and .set file path are required.');
+      return;
+    }
+
+    try {
+      const resp = await fetch('/api/ea/register', {
+        method: 'POST',
+        headers: {'Content-Type': 'application/json'},
+        body: JSON.stringify({ name, ex5_file: file || name, set_template: set, symbol, timeframe, mode: 'generic' }),
+      });
+      const result = await resp.json();
+      if (result.ok) {
+        hideAddEAModal();
+        // Add to dropdown immediately without reload
+        const sel = document.getElementById('ea_name');
+        const existing = [...sel.options].find(o => o.value === name);
+        if (!existing) {
+          const opt = new Option(name, name);
+          sel.add(opt);
+        }
+        sel.value = name;
+        document.getElementById('scan-status').textContent = `"${name}" registered ✓`;
+        document.getElementById('scan-status').style.color = '#00d4aa';
+        // Reload params for this EA
+        if (typeof loadEAParams === 'function') loadEAParams(name);
+      } else {
+        alert('Error: ' + (result.error || 'Registration failed'));
+      }
+    } catch(e) {
+      alert('Network error: ' + e.message);
+    }
+  }
+
+  async function loadEAParams(eaName) {
+    const grid = document.getElementById('param-grid');
+    if (!grid) return;
+    grid.innerHTML = '<span style="color:#64748b;font-size:0.82rem">Loading parameters...</span>';
+    try {
+      const resp = await fetch('/api/ea_params?ea=' + encodeURIComponent(eaName));
+      const params = await resp.json();
+      if (params.error) { grid.innerHTML = `<span style="color:#ef4444;font-size:0.82rem">${params.error}</span>`; return; }
+      if (!params.length) { grid.innerHTML = '<span style="color:#64748b;font-size:0.82rem">No optimizable parameters found in .set file.</span>'; return; }
+      grid.innerHTML = params.map(p => `
+        <label class="param-check">
+          <input type="checkbox" name="selected_params" value="${p.name}" ${p.optimize ? 'checked' : ''}>
+          <span title="${p.range || ''}">${p.name.replace('Inp','')}</span>
+        </label>
+      `).join('');
+    } catch(e) {
+      grid.innerHTML = `<span style="color:#ef4444;font-size:0.82rem">Error loading params: ${e.message}</span>`;
+    }
+  }
+
+  // Reload params + symbol/timeframe when EA selection changes
+  document.getElementById('ea_name').addEventListener('change', function() {
+    loadEAParams(this.value);
+  });
+
+  function toggleAutonomous(btn) {
+    const isOn = btn.style.background === 'rgb(79, 70, 229)' || btn.classList.contains('on');
+    if (isOn) {
+      btn.style.background = 'rgba(255,255,255,0.12)';
+      btn.classList.remove('on');
+      btn.querySelector('span') && (btn.querySelector('span').style.transform = '');
+      document.getElementById('autonomous-controls').style.display = 'none';
+      document.getElementById('autonomous-mode-val').value = 'false';
+    } else {
+      btn.style.background = '#4f46e5';
+      btn.classList.add('on');
+      document.getElementById('autonomous-controls').style.display = 'block';
+      document.getElementById('autonomous-mode-val').value = 'true';
+    }
+    // Maintain the ::after pseudo-element position via class
+    btn.style.setProperty('--toggle-x', isOn ? '0px' : '20px');
+  }
+
+  // ── Toast helper for inline validation feedback ────────────────────────
+  function showSetupError(msg) {
+    let toast = document.getElementById('setup-toast');
+    if (!toast) {
+      toast = document.createElement('div');
+      toast.id = 'setup-toast';
+      toast.style.cssText = 'position:fixed;top:20px;right:20px;background:rgba(239,68,68,0.95);color:white;padding:0.8rem 1.2rem;border-radius:8px;font-size:0.85rem;font-weight:600;z-index:9999;box-shadow:0 4px 12px rgba(0,0,0,0.3);max-width:380px;line-height:1.4;';
+      document.body.appendChild(toast);
+    }
+    toast.textContent = msg;
+    toast.style.display = 'block';
+    clearTimeout(toast._timer);
+    toast._timer = setTimeout(() => { toast.style.display = 'none'; }, 5000);
+  }
+
+  function validateSetup(data) {
+    if (!data.ea_name || !data.ea_name.trim()) {
+      return 'Please select an EA before starting.';
+    }
+    if (!data.symbol || !data.timeframe) {
+      return 'Symbol and timeframe are required.';
+    }
+    const ds = (s) => new Date((s || '').replace(/\./g, '-'));
+    const ts = ds(data.train_start), te = ds(data.train_end);
+    const vs = ds(data.val_start),   ve = ds(data.val_end);
+    if (isNaN(ts) || isNaN(te) || isNaN(vs) || isNaN(ve)) {
+      return 'All four dates must be valid (YYYY-MM-DD).';
+    }
+    if (ts >= te) return 'Training start must come before training end.';
+    if (vs >= ve) return 'Validation start must come before validation end.';
+    if (vs < te) return 'Validation period should start after the training period (walk-forward).';
+    if (data.budget_minutes < 1) return 'Time budget must be at least 1 minute.';
+    if (!data.selected_params || data.selected_params.length === 0) {
+      return 'Pick at least one parameter to optimize.';
+    }
+    if (data.autonomous_mode) {
+      if (data.autonomous_max_iterations < 1 || data.autonomous_max_iterations > 100) {
+        return 'AI max iterations must be between 1 and 100.';
+      }
+      if (data.target_profit_factor < 1) return 'Target profit factor must be ≥ 1.';
+      if (data.target_max_drawdown_pct <= 0 || data.target_max_drawdown_pct > 100) {
+        return 'Target max drawdown must be between 0 and 100 (%).';
+      }
+    }
+    return null;  // valid
+  }
+
   document.getElementById('setup-form').addEventListener('submit', async (e) => {
     e.preventDefault();
     const btn = document.getElementById('start-btn');
-    btn.disabled = true;
-    btn.innerHTML = '<span>⏳</span> Starting...';
+    const restoreBtn = () => {
+      btn.disabled = false;
+      btn.innerHTML = '<span>⚡</span> Start Optimization';
+    };
 
     const form = e.target;
+    const autonomousOn = document.getElementById('autonomous-mode-val').value === 'true';
     const data = {
       ea_name:        form.ea_name.value,
       symbol:         form.symbol.value,
@@ -438,8 +822,23 @@
       budget_minutes: parseInt(form.budget_minutes.value),
       selected_params: [...form.querySelectorAll('input[name=selected_params]:checked')]
                          .map(cb => cb.value),
+      // Autonomous loop
+      autonomous_mode:           autonomousOn,
+      autonomous_max_iterations: parseInt(document.getElementById('ai-max-iter').value) || 10,
+      target_profit_factor:      parseFloat(document.getElementById('ai-target-pf').value) || 1.5,
+      target_max_drawdown_pct:   parseFloat(document.getElementById('ai-target-dd').value) || 20.0,
+      target_min_calmar:         parseFloat(document.getElementById('ai-target-calmar').value) || 0.5,
     };
 
+    const validationError = validateSetup(data);
+    if (validationError) {
+      showSetupError(validationError);
+      return;
+    }
+
+    btn.disabled = true;
+    btn.innerHTML = '<span>⏳</span> Starting...';
+
     try {
       const resp = await fetch('/api/start', {
         method: 'POST',
@@ -450,14 +849,12 @@
       if (result.ok) {
         window.location.href = '/dashboard';
       } else {
-        alert('Could not start: ' + (result.msg || 'Unknown error'));
-        btn.disabled = false;
-        btn.innerHTML = '<span>⚡</span> Start Optimization';
+        showSetupError('Could not start: ' + (result.msg || 'Unknown error'));
+        restoreBtn();
       }
     } catch(err) {
-      alert('Network error: ' + err.message);
-      btn.disabled = false;
-      btn.innerHTML = '<span>⚡</span> Start Optimization';
+      showSetupError('Network error: ' + err.message);
+      restoreBtn();
     }
   });
 </script>