Project Structure for AI

While AI coding assistants are powerful, they are not magic. They rely on the structure and organization of your project to understand its architecture, conventions, and constraints. A well-organized project is easier for an AI to navigate, leading to more accurate and contextually-aware suggestions.

This guide covers best practices for organizing your files and configuration to maximize the effectiveness of both Cursor IDE and Claude Code.

The Power of AI-Specific Configuration

Both Cursor and Claude Code utilize special configuration files to provide them with high-level, persistent context about your project. These files are the single most important element in structuring your project for AI.

Cursor: .cursor/rules/

Cursor uses a .cursor/rules/ directory to store project-specific guidelines. These .mdc files can define coding standards, architectural patterns, and reusable prompts. You can have a global set of rules at the project root and more specific rules in subdirectories (e.g., frontend/.cursor/rules/).

Claude Code: CLAUDE.md

Claude Code relies on CLAUDE.md files. Like Cursor’s rules, these can be hierarchical. A CLAUDE.md in the root provides global context, while nested ones in directories like backend/ or services/ provide more specific instructions when the AI is working within those parts of the codebase.

Key takeaway: Use these configuration files to document your project’s “unwritten rules” so the AI can follow them.

Best Practices for File Organization

1. Use Hierarchical Configuration. For any non-trivial project, especially monorepos, use nested configuration files.

   • Root Level: Define project-wide standards, dependencies, and architectural overview.
   • Service/Module Level: In frontend/, backend/, or packages/ subdirectories, add specific rules for that part of the codebase (e.g., “Always use React Server Components in the frontend,” or “The backend uses the Repository pattern for data access.”).

2. Tell the AI What to Ignore. Just as important as telling the AI what to look at is telling it what to ignore.

   • .gitignore: Both tools respect .gitignore. Ensure it’s comprehensive to keep node_modules, build artifacts, and environment files out of the AI’s context.
   • Tool-Specific Ignores: Use .cursor/ignored-files for Cursor or similar configurations to explicitly prevent the AI from accessing sensitive files or directories that might not be in .gitignore (like large data files).

3. Co-locate Documentation. Keep documentation as close to the code as possible. If you have a complex module, a README.md inside that module’s directory is invaluable context for an AI assistant. You can use your AI assistant to help generate and maintain this documentation.

4. Manage Multi-Repository Projects. When working on a feature that spans multiple repositories (e.g., a service and a shared library):

   • Cursor: Use Multi-Root Workspaces to open all relevant repositories in a single window.
   • Claude Code: Use the --add-dir flag or the /add-dir command to bring multiple project directories into a single session’s context.

5. Break Down Large Files. While modern AI can handle very large files, performance and accuracy improve with smaller, more focused modules. If you have a file that’s thousands of lines long, consider asking the AI to help you refactor it into smaller, more manageable pieces. This not only helps the AI but also improves the maintainability of your code.

By adopting these organizational strategies, you provide a clear and structured environment for your AI assistant, enabling it to function as a true, context-aware member of your development team.