# Glue Coding Methodology

## **1. Definition of Glue Coding**

**Glue coding** is a new type of software construction method, whose core idea is:

> **Almost entirely reusing mature open-source components, combining them into a complete system with minimal "glue code".**

It emphasizes "connecting" rather than "creating", and is particularly 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 If it can be avoided, don't write it; if it can be minimized, minimize it.**

Any function with a mature existing implementation should not be reinvented.

### **3.2 If it can be copied and pasted, copy and paste.**

Directly copying and using community-tested code is a normal engineering process, not laziness.

### **3.3 Stand on the shoulders of giants, rather than trying to become a giant.**

Utilize existing frameworks, rather than trying to write a "better wheel" yourself.

### **3.4 Do not modify the original repository code.**

All open-source libraries should remain as immutable as possible, used as black boxes.

### **3.5 Minimize custom code.**

The code you write only serves for:

*   Combination
*   Calling
*   Encapsulation
*   Adaptation

This is the so-called **glue layer**.

## **4. Standard Process of Glue Coding**

### **4.1 Clarify Requirements**

Break down the system's functionalities into individual requirements.

### **4.2 Use GPT/Grok to Decompose Requirements**

Let AI refine requirements into reusable modules, capabilities, and corresponding subtasks.

### **4.3 Search for Existing Open-Source Implementations**

Utilize GPT's internet capabilities (like Grok):

*   Search for corresponding GitHub repositories based on each sub-requirement
*   Check for reusable components
*   Compare quality, implementation methods, licenses, etc.

### **4.4 Download and Organize Repositories**

Pull selected repositories locally and categorize them.

### **4.5 Organize by Architectural System**

Place these repositories into the project structure, for example:

```
/services  
/libs  
/third_party  
/glue  
```

And emphasize: **Open-source repositories, as third-party dependencies, must absolutely not be modified.**

### **4.6 Write the Glue Layer Code**

The glue code's functions include:

*   Encapsulating interfaces
*   Unifying input and 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-verified mature code.

### **5.2 Extremely Fast Development Speed**

A large number of functionalities can be directly reused.

### **5.3 Reduced Costs**

Time costs, maintenance costs, and learning costs are 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, decomposing, and integrating, serving as 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       | "Inventing wheels"      | "Combining wheels" |

## **7. Typical Application Scenarios for Glue Coding**

*   Rapid prototyping
*   Small teams building large systems
*   AI applications/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 large amounts 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.