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Open Source Changes: - Add prompt loader functions for strategy prompts - Add factor values persistence (parquet) in factor_runner.py - Add CLI command: predix build-strategies-ai - Integrate strategy building into QuantRDLoop (every 50 factors) - Add StrategyBuilder design documentation Closed Source Files (NOT committed, in local/): - strategy_coster.py - Main CoSTEER loop for strategies - strategy_evaluator.py - Walk-forward backtesting - strategy_runner.py - Strategy execution - strategy_discovery_v1.yaml - LLM prompts Usage: predix build-strategies-ai # Build from top 50 factors predix build-strategies-ai -t 100 # Use top 100 factors predix build-strategies-ai -l 10 # 10 improvement loops The system: 1. Loads top factors with time-series values 2. LLM generates strategy hypotheses 3. LLM writes strategy code (entry/exit rules) 4. Backtests strategy with walk-forward validation 5. LLM gets feedback and improves 6. Repeats until profitable strategy found