Cursor + Windsurf Settings to 5x AI’s Output Quality (Works with VS Code too)

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AI Summary

Video Summary: Enhancing AI Coding Assistants with Context Rules

Introduction

• AI requires concrete context to function effectively in real-world applications.
• The video demonstrates how a simple rules file can improve the performance of AI coding assistants across various code editors.

Context Rules in Code Editors

• Major code editors support context rules but store them differently:
  • VS Code: GitHub Code Pilot instructions
  • Cursor: cursor rules file at the root of the repository
  • Wind Surf: do wind surve rules file

Creating and Using a Rules File

• A rules file includes context that is automatically included in AI prompts.
• Example: Adding “ho ho ho” to the beginning of every output.
• The rules file should explicitly state the rule being applied for clarity and verification.

Contents of a Rules File

1. Project Context: A brief description of the project’s purpose.
2. Codebase Structure: Outlines the structure of the code, such as monorepo setup, front-end, back-end, and shared components.
3. Tech Stack: Specifies the technologies and libraries used to prevent the AI from introducing unwanted dependencies.
4. Specific Implementations: Details about project-specific requirements, such as Chrome extension manifest version or database ORM conventions.

Tips for Effective Rules Files

• Keep the rules file concise to avoid confusing the AI.
• Update the file iteratively as you identify AI mistakes or new project requirements.
• Use the rules file to correct consistent AI errors, like deprecated commands.
• Include git commit message preferences to maintain a clean git history.
• Specify when to include comments in the code, focusing on complex logic and critical system performance documentation.

Principles for Maintaining Rules Files

1. Conciseness: Only add rules that address consistent AI mistakes and critical project context.
2. Continuous Updates: Edit the file as new problems are discovered and as part of the development process.

Future Improvements for AI Context Management

• The ability to conditionally include context files based on the task (e.g., database, UI).
• Automatic addition of context to AI memory based on user interactions, similar to ChatGPT’s memory feature.

Conclusion

• By following the outlined approach, AI coding assistants can become more reliable and consistent.
• The video encourages viewers to check out other AI coding assistant pro tips.

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Note: The summary does not include any URLs or CLI commands as none were provided in the transcript.