AI Documentation Tools
Mintlify: generates and hosts beautiful API documentation with AI. Swimm: keeps documentation in sync with code changes. GitHub Copilot: generates inline comments and docstrings. Cursor: ask it to document functions or generate READMEs from codebase analysis.
Inline Code Documentation
AI excels at generating JSDoc comments, Python docstrings, and function-level documentation. It reads the code, understands parameters and return types, and generates descriptive comments. This is the lowest-effort, highest-value use of AI documentation.
README Generation
AI can generate comprehensive README files from repository analysis — installation steps, usage examples, API reference, and contributing guidelines. Provide your project context and let AI structure the document. Review for accuracy and add project-specific details manually.
API Documentation
Generate OpenAPI/Swagger specs from route handlers. AI analyzes endpoints, parameters, response types, and error codes. Tools like Mintlify transform specs into polished documentation sites. Keep specs in sync with code using CI checks.
Limitations
AI doesn't understand your business domain. It can describe what code does, not why. Architecture decisions, design rationale, and operational guides need human authorship. Use AI for the mechanical parts (what parameters, what returns) and write the strategic parts yourself.
Conclusion
AI documentation tools save hours on the mechanical parts of documentation. Start by generating inline docs for your undocumented codebase, then use AI for README and API docs. Always review and enrich with human context — AI describes the code, you explain the intent.