How to improve code productivity with AI: A detailed guide

How to improve code productivity with AI: A detailed guide
Introduction
In team cooperation and software development, more and more developers rely on AI tools to generate code. However, how to make AI tools more in line with project needs? This article will start from several key aspects and teach you how to guide AI to generate more efficient and standardized code by setting standards and rules.
1. Why is the setting of project background important?
Clear project background can help AI understand the code context and choose appropriate frameworks, syntax and structures.
Example

# Project Background 
This is a multi-language blog application based on Next.js, which supports multi-language switching functionality. 

2. Why is defining coding standards important? Consistent coding styles can improve team collaboration efficiency and reduce problems in code reviews. Example

# Coding Standards 
- Use functional components and Hooks instead of class components. 
- Prefer using `const` to declare variables. 
- Use camelCase for variable and function names and PascalCase for component names.

Why is it important to specify preferred libraries and frameworks? If there is no clear library selection, AI may introduce unnecessary third-party dependencies and increase subsequent maintenance costs. Example

# Preferred libraries 
- Using Next.js for navigation 
- Using next-intl for internationalization 
- Using Tailwind CSS for style design

Why is providing file structure information important? A clear directory structure helps generate correct paths and reduces debugging work due to path errors. Example

# File structure 
-components: Reusable UI components 
-app/[locale]: Pages supporting multiple languages 
-data/blog: Location for storing blog content 
-app/api: API service function

5. Why is the performance optimization guide important? Performance optimization is the core of high-quality code. Example

# Performance Optimization Guide 
- Optimize Pure Function Components with React.memo 
- Implement Lazy Loading for Routing Components 
- Optimize Dependencies Array in useEffect Hook

Why are test requirements important? The automatically generated code also needs to be testable. Example

# Testing Requirements 
- Use Jest and React Testing Library to write unit tests. 
- The coverage should reach more than 80%. 
- Generate snapshot tests for UI components.

7. Why is document specification important? A standardized document is an important source of team knowledge accumulation. Example

# Document Specification 
- Use JSDoc format to write comments. 
- Must include PropTypes validation. 
- Each directory must contain a README file in both Chinese and English.

Why is error handling preference important? If error handling is ignored, the code may cause serious problems during runtime. Example

# Error Handling 
- Using try/catch blocks for asynchronous operations 
- Implementing a global error boundary component

Summarizing by setting the above rules, AI tools can not only generate efficient code but also improve code quality and reduce team communication costs. Whether it is a startup team or a mature enterprise, these settings can help you better use AI to empower the development process. Relevant resources

• • “awesome-cursorrules”: Sums up excellent.cursorrules cases for developers to refer to
• • “Cursorlist”: A tool platform for sharing and collecting various rule settings
• • “Cursor Directory”: Includes rich rule templates and cases that can be quickly applied to projects.

If you have other optimization techniques for AI, feel free to share them in the comment area!