Article Author: Programmer Wan Feng | AI Programming Evangelist | Focused on AI Tool Reviews and Teaching

400k+ followers across platforms, 6 years Python development experience, author of open source project python-office

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Hello everyone, this is Programmer Wan Feng.

Today I bring you a special tutorial on Kimi Coding Plan, focusing on how to use its 128K ultra-long context to process large code projects—this is Kimi's unique strength.

1. Kimi's Killer Feature: 128K Context

What is 128K Context?

Simply put, it's how much content AI can "remember" at once. Regular AI might only see a few K tokens, but Kimi can see 128K tokens.

128K tokens is approximately:

  • 100,000 characters (Chinese and English mixed)
  • Hundreds of source code files
  • All the code of a small to medium-sized project

Why is this important?

Previously, when using AI to analyze code, you needed to:

  1. Split the code into small pieces
  2. Feed it to AI piece by piece
  3. AI might "forget" previous content

Now with Kimi, you can:

  1. Feed all the project code at once
  2. AI understands everything in one go
  3. Get more accurate analysis

2. Hands-on: Analyzing Large Projects with Kimi

Scenario: Analyzing a Python Project

Assume you have a Python project containing:

  • main.py
  • utils.py
  • models.py
  • config.py
  • 20 other files

Step 1: Prepare the Code

Organize the files you want AI to analyze (can be compressed into one folder).

Step 2: Describe Your Requirements

Give Kimi a clear task:

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Help me analyze this Python project:
1. What is the project structure?
2. Where is the core business logic?
3. What are potential bugs or optimization points?

Step 3: Get Analysis Results

Kimi will provide analysis based on the complete context, which is much more accurate than feeding code piece by piece.

3. Other Uses of Kimi

1. Code Review

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Help me review the entire project code and find:
- Potential bugs
- Security risks
- Code style issues

2. Large-scale Refactoring

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I want to refactor this project, changing from MVC to Clean Architecture,
help me analyze which places need changes?

3. Learning a New Project

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I just took over this project, help me:
1. Understand the project architecture
2. Find the core modules
3. Explain how to get started

4. FAQ

Q1: Is 128K Enough?

For most projects, 128K is more than enough. Even for large projects, you can process them in batches.

Q2: How About Response Speed?

When processing large amounts of context, response time will be longer than short text, but usually within 10 seconds.

Q3: Is the Price Expensive?

Specific prices are based on the official website, but considering the convenience of long context, the cost-effectiveness is quite good.

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Author: Programmer Wan Feng, same name across all platforms, focused on AI tool reviews and Python automation office teaching.

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