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# 🧬 Glue Coding
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> **The holy grail and silver bullet of software engineering – it's finally here.**
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---
## 🚀 Disruptive Manifesto
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**Glue Coding is not a technology, but a revolution.**
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It might perfectly solve the three fatal flaws of Vibe Coding:
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| Pain Points of Traditional Vibe Coding | Glue Coding's Solution |
|:---|:---|
| 🎭 **AI Hallucinations** - Generating non-existent APIs, incorrect logic | ✅ **Zero Hallucinations** - Only using validated, mature code |
| 🧩 **Complexity Explosion** - The larger the project, the more out of control it becomes | ✅ **Zero Complexity** - Every module is a time-tested wheel |
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| 🎓 **High Barrier to Entry** - Requires deep programming skills to master AI | ✅ **Barrier Disappears** - You only need to describe "how to connect" |
---
## 💡 Core Concept
```
Traditional Programming: Humans write code
Vibe Coding: AI writes code, humans review code
Glue Coding: AI connects code, humans review connections
```
### Paradigm Shift
**A fundamental shift from "generation" to "connection":**
- ❌ No longer letting AI generate code from scratch (the source of hallucinations)
- ❌ No longer reinventing the wheel (the source of complexity)
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- ❌ No longer requiring you to understand every line of code (the source of high barriers)
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- ✅ Only reusing mature, production-validated open-source projects
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- ✅ AI's sole responsibility: understanding your intent and connecting modules
- ✅ Your sole responsibility: clearly describing "what is the input, what is the desired output"
---
## 🏗️ Architectural Philosophy
```
┌─────────────────────────────────────────────────────────┐
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│ Your Business Needs │
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└─────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────┐
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│ AI Glue Layer │
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│ │
│ "I understand what you want to do, let me connect these blocks" │
│ │
└─────────────────────────────────────────────────────────┘
│
┌────────────────┼────────────────┐
▼ ▼ ▼
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
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│ Mature Module A │ │ Mature Module B │ │ Mature Module C │
│ (100K+ ⭐) │ │ (Production Validated) │ │ (Official SDK) │
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└─────────────┘ └─────────────┘ └─────────────┘
```
**Entity** : Mature open-source projects, official SDKs, time-tested libraries
**Link** : AI-generated glue code, responsible for data flow and interface adaptation
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**Function** : Your described business objective
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---
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## 🎯 Why is this the Silver Bullet?
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### 1. Hallucination Problem → Completely Disappears
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AI no longer needs to "invent" anything. It only needs to:
- Read Module A's documentation
- Read Module B's documentation
- Write the data transformation from A to B
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**This is what AI excels at, and what is least prone to errors.**
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### 2. Complexity Problem → Transferred to the Community
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Behind each module are:
- Thousands of Issue discussions
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- Hundreds of contributors' wisdom
- Years of production environment refinement
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**You are not managing complexity, you are standing on the shoulders of giants.**
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### 3. Barrier to Entry Problem → Reduced to a Minimum
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You don't need to understand:
- Underlying implementation principles
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- Best practice details
- Edge case handling
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You just need to speak human language:
> "I want to process Telegram messages with GPT and save them to PostgreSQL"
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**AI will help you find the most suitable wheels and then glue them together.**
---
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## 📋 Practical Workflow
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```
1. Clarify Goal
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└─→ "I want to implement XXX function"
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2. Find Wheels
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└─→ "Are there any mature libraries/projects that have done something similar?"
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└─→ Let AI help you search, evaluate, and recommend
3. Understand Interfaces
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└─→ Feed the official documentation to AI
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└─→ AI summarizes: what is the input, what is the output
4. Describe Connection
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└─→ "The output of A should become the input of B"
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└─→ AI generates glue code
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5. Verify Run
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└─→ Runs successfully → Done
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└─→ Error → Give the error to AI, continue gluing
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```
---
## 🔥 Classic Case Study
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### Case: Polymarket Data Analysis Bot
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**Requirement** : Real-time acquisition of Polymarket data, analysis, and pushing to Telegram
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**Traditional Approach** : Write a crawler from scratch, write analysis logic, write a Bot → 3000 lines of code, 2 weeks
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**Glue Approach** :
```
Wheel 1: polymarket-py (Official SDK)
Wheel 2: pandas (Data Analysis)
Wheel 3: python-telegram-bot (Message Push)
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Glue Code: 50 lines
Development Time: 2 hours
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```
---
## 📚 Further Reading
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- [语言层要素 ](./语言层要素.md ) - 8 Levels of Understanding 100% Code
- [胶水开发提示词 ](../../prompts/coding_prompts/胶水开发.md )
- [项目实战:polymarket-dev ](../项目实战经验/polymarket-dev/ )
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---
## 🎖️ Summary
> **If you can copy, don't write; if you can connect, don't build; if you can reuse, don't originate.**
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Glue Coding is the ultimate evolution of Vibe Coding.
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It's not laziness, but **the highest manifestation of engineering wisdom** –
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Using the least amount of original code to leverage the greatest productivity.
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**This is the silver bullet software engineering has been waiting for for 50 years.**
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---
*"The best code is no code at all. The second best is glue code."*
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# Glue Coding Methodology
## **1. Definition of Glue Coding**
**Glue coding** is a new software construction method, whose core idea is:
> **Almost entirely reusing mature open-source components, combining them into a complete system with a minimal amount of "glue code".**
It emphasizes "connection" rather than "creation", especially efficient in the AI era.
## **2. Background**
Traditional software engineering often requires developers to:
* Design architecture
* Write logic themselves
* Manually handle various details
* Reinvent the wheel
This leads to high development costs, long cycles, and low success rates.
However, the current ecosystem has fundamentally changed:
* Thousands of mature open-source libraries on GitHub
* Frameworks covering various scenarios (Web, AI, Distributed, Model Inference...)
* GPT / Grok can help search, analyze, and combine these projects
In this environment, writing code from scratch is no longer the most efficient way.
Thus, "glue coding" has emerged as a new paradigm.
## **3. Core Principles of Glue Coding**
### **3.1 Don't write what can be avoided, write as little as possible**
Any functionality with a mature existing implementation should not be reinvented.
### **3.2 Copy-paste whenever possible**
Directly copying and using community-validated code is a normal engineering process, not laziness.
### **3.3 Stand on the shoulders of giants, don't try to be a giant**
Utilize existing frameworks instead of trying to write a "better wheel" yourself.
### **3.4 Do not modify original repository code**
All open-source libraries should ideally remain immutable, used as black boxes.
### **3.5 The less custom code, the better**
Your written code only serves to:
* Combine
* Call
* Encapsulate
* Adapt
Which is the so-called **glue layer** .
## **4. Standard Workflow of Glue Coding**
### **4.1 Clarify Requirements**
Break down the system's functionality into individual requirements.
### **4.2 Use GPT/Grok to Deconstruct Requirements**
Let AI refine requirements into reusable modules, capabilities, and corresponding subtasks.
### **4.3 Search for Existing Open-Source Implementations**
Leverage GPT's internet capabilities (e.g., Grok):
* Search for corresponding GitHub repositories for each sub-requirement.
* Check for reusable components.
* Compare quality, implementation methods, licenses, etc.
### **4.4 Download and Organize Repositories**
Pull the selected repositories locally and organize them by category.
### **4.5 Organize According to Architectural System**
Place these repositories into the project structure, for example:
```
/services
/libs
/third_party
/glue
```
And emphasize: **Open-source repositories are third-party dependencies and must never be modified.**
### **4.6 Write Glue Layer Code**
The role of glue code includes:
* Encapsulating interfaces
* Unifying input/output
* Connecting different components
* Implementing minimal business logic
The final system is composed of multiple mature modules.
## **5. Value of Glue Coding**
### **5.1 Extremely High Success Rate**
Because it uses community-validated mature code.
### **5.2 Extremely Fast Development Speed**
A large amount of functionality can be directly reused.
### **5.3 Reduced Costs**
Time cost, maintenance cost, and learning cost are all significantly reduced.
### **5.4 More Stable System**
Relies on mature frameworks rather than individual implementations.
### **5.5 Easy to Extend**
Capabilities can be easily upgraded by replacing components.
### **5.6 Strong Synergy with AI**
GPT can assist in searching, deconstructing, and integrating, making it a natural enhancer for glue engineering.
## **6. Glue Coding vs. Traditional Development**
| Project | Traditional Development | Glue Coding |
| ----------- | ------------------------ | ------------- |
| Feature Implementation | Write yourself | Reuse open-source |
| Workload | Large | Much smaller |
| Success Rate | Uncertain | High |
| Speed | Slow | Extremely fast |
| Error Rate | Prone to pitfalls | Uses mature solutions |
| Focus | "Building wheels" | "Combining wheels" |
## **7. Typical Application Scenarios for Glue Coding**
* Rapid prototype development
* Small teams building large systems
* AI application/model inference platforms
* Data processing pipelines
* Internal tool development
* System Integration
## **8. Future: Glue Engineering will become the new mainstream programming method**
As AI capabilities continue to strengthen, future developers will no longer need to write a lot of code themselves, but rather:
* Find wheels
* Combine wheels
* Intelligently connect components
* Build complex systems at extremely low cost
Glue coding will become the new standard for software productivity.