The AI development revolution has democratized coding – even absolute beginners can now create functional apps. Inspired by Li Jigang’s viral “Book of Answers” and “Divination” prompts, I embarked on creating my first WeChat mini program. Here’s my battle-tested guide to transforming AI magic into a real-world application.

01 Tools of the Trade: Setting Up Your Arsenal

I. WeChat Mini Program Development Setup

1. Install Official Dev Tools
   Download the WeChat Developer Tools from Official Portal. This all-in-one suite includes:

• Real-time preview simulator
• Debugging console with network monitoring
• Automatic WXML/WXSS compilation

1. Initialize Project Framework
   Create new project → Select “Empty Template” → Configure:

• Project name: “AI Oracle” (or your custom name)
• AppID: Obtain from WeChat Official Platform (requires verified account)
• Enable ES6/ES7 transpilation

II. Cursor AI Development Configuration

1. Install Cursor (The AI Pair Programmer)
   Get the latest version from cursor.com. Pro tip: Enable “Developer Mode” during installation for advanced features.

1. Localization Setup
   Ctrl+Shift+P → “Configure Display Language” → Install Chinese Simplified package → Restart IDE

1. Activate Composer (Secret Weapon)
   File → Preferences → Settings → Search “Composer” → Enable multi-file editing and batch generation

1. Project Integration
   File → Open Folder → Select your WeChat project directory → Activate WXML/WXSS syntax highlighting

02 AI-Driven Development Workflow

Step 1: Requirements Specification

Create readme.md with:

1. Role: Senior WeChat Mini Program UI Engineer  
2. Task: Implement input-output interface for AI API integration  
3. Tech Stack:  
   - Frontend: WXML/WXSS/JavaScript  
   - Backend: SiliconFlow API (LLM integration)  
4. Requirements:  
   - Clean material design interface  
   - Input validation system  
   - Loading state management  
   - Error handling with user feedback  

Step 2: AI Code Generation

1. Open readme.md
2. Ctrl+I → Select Claude-3.5-Sonnet-20241022 (Best for Chinese context)
3. Prompt: “Generate complete implementation per spec”

AI Output Analysis:

• Automatically creates index.wxml, index.wxss, index.js, index.json
• Implements basic API call structure
• Sets up event listeners

Step 3: SiliconFlow API Integration

1. Register at SiliconFlow Cloud
2. Obtain API Key → Configure in config.js:

   module.exports = {  
   API_ENDPOINT: 'https://api.siliconflow.cn/v1/chat',  
   API_KEY: 'sk-your-key-here'  
   }  

Step 4: Iterative Refinement

Common Debugging Scenarios:

• CORS Issues: Configure domain whitelist in WeChat backend
• Layout Bugs: Use Chrome DevTools-like inspector in WeChat IDE
• API Throttling: Implement exponential backoff retry logic

03 Final Implementation Showcase

Core Features Achieved:

1. Clean Material Design UI
2. Real-time AI Response Streaming
3. Session History Preservation
4. Error Boundary Handling

Pro Tips for Production Readiness

1. Performance Optimization

• Implement virtual scrolling for long responses
• Add WebSocket support for faster updates
• Use WXS for computationally heavy tasks

1. Security Enhancements

• Encrypt local storage using WeChat’s wx.setStorageSync
• Implement JWT token rotation for API calls
• Add rate limiting to prevent abuse

1. App Store Compliance

• Include privacy policy page
• Implement content filtering system
• Add user feedback/report mechanism

This journey proves that with modern AI tools like Cursor, even non-coders can ship functional apps in hours rather than months. The future of development isn’t just about writing code – it’s about effectively directing AI collaborators to materialize your vision.