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

Summary

This video explores how to improve AI coding assistants by using context-specific rules files. By clearly defining project structure, tech stack, commit guidelines, and preferences, developers can guide AI to generate better, more consistent code. The video covers how to add and update these rules iteratively, ensuring AI adapts to your project’s needs over time. With examples like integrating code formatting preferences, handling git commits, and using AI for Chrome extension projects, the video demonstrates practical strategies for developers to make their AI tools smarter and more reliable in real-world applications.

Takeaways

• 😀 AI assistants require clear, well-defined context to generate reliable outputs for real-world projects.
• 😀 A rules file can transform your AI coding assistant into a more reliable development partner by providing key project context.
• 😀 Different coding editors (VS Code, Cursor, WindSurf) support similar rules files that help guide AI behavior.
• 😀 Keeping rules files concise is crucial—too much context can confuse the AI and make the code generation less effective.
• 😀 Regularly updating the rules file as your project evolves ensures that the AI's output stays relevant and accurate.
• 😀 Providing explicit context in rules files for project structure, tech stack, and behavior preferences leads to better code quality.
• 😀 Rules files can help enforce project-specific conventions, such as commit message formats, code documentation, and dependencies.
• 😀 AI assistants work best when they are explicitly told how to handle specific cases, like Chrome extension details or database usage.
• 😀 Using concise project descriptions in rules files avoids confusion and helps AI generate the right code, even for complex tasks.
• 😀 It's important to track and address common mistakes made by the AI, such as using deprecated commands or incorrect libraries.
• 😀 The future of AI assistants lies in improving context management, such as automatically including relevant files and adapting based on previous interactions.

Q & A

Why is context important for AI in coding assistance?

Context is crucial because AI cannot make accurate guesses without sufficient information. By providing a concrete context, developers can ensure AI generates code that aligns with the project's goals, structure, and requirements.

How can a rules file improve AI's reliability in coding assistance?

A rules file helps guide the AI by setting explicit instructions and preferences for code generation, such as project structure, technologies used, and specific coding standards. This makes the AI a more reliable partner by reducing errors and ensuring consistency.

What is the purpose of stating the rule in the output of AI?

Stating the rule in the output helps ensure transparency and allows developers to easily verify if the AI has followed the intended instructions. This explicit feedback allows for easier debugging and ensures that the AI is working as expected.

How does the project context section in the rules file help AI?

The project context section provides a high-level overview of the project's purpose, helping the AI understand the problem being solved and the desired outcome. This allows the AI to generate more relevant and targeted code.

What is the significance of the project directory structure for AI?

Defining the project directory structure helps the AI understand the organization of the codebase, enabling it to generate code in the correct location and follow the project's conventions, ensuring consistency and avoiding mistakes.

Why should developers specify their tech stack in the rules file?

Specifying the tech stack ensures that the AI understands the tools and frameworks being used, preventing it from introducing unsupported or unnecessary dependencies. This context ensures that the generated code aligns with the project's environment.

What are the benefits of keeping the rules file concise?

A concise rules file prevents the AI from becoming overwhelmed with excessive information, reducing the risk of confusion and errors. It also makes the file easier to maintain and update, ensuring it remains effective throughout the development process.

How can AI assist with Git commit messages based on the rules file?

AI can generate consistent and well-structured Git commit messages by following the guidelines specified in the rules file. This ensures a clean and organized commit history, making it easier to track the progress of the project.

What role does the AI play in maintaining project documentation like the README file?

AI can automatically update project documentation, such as the README file, based on changes in the codebase. For example, if a library is modified or a significant change is made, the AI can update the README to reflect those changes.

How can developers ensure that AI generates only relevant comments in code?

By specifying in the rules file that AI should only add comments for complex logic or performance-critical code, developers can avoid inconsistent or unnecessary comments. This keeps the codebase clean and focused on essential documentation.