In my 15+ years as a developer, one of the most frustrating problems I've seen across teams is outdated documentation. I’ll be honest, I skip it myself. You ship a feature and move on. Then a month later, someone is onboarding or debugging and runs into stale docs that no longer reflect the code.

I tried fixing this with tools like Swagger and Sphinx-autodoc, but they only work for narrow use cases like OpenAPI or annotations. They don’t help with the high-level stuff like onboarding tutorials, SDK guides, or user-facing examples. You still have to keep things like docstrings in sync, and it’s a manual burden.

LLMs helped a bit. Tools like Cursor and Copilot let you prompt for doc updates, and they work to some extent. But you have to remember to prompt after every change, figure out the right context manually, and hope your teammates don’t overwrite things in their own AI sessions. And if you're not careful, the updated docs lose their original structure or style.

So I built DeepDocs — a GitHub-native AI app that keeps your documentation in sync with your codebase automatically. Once installed, it listens to your commits, detects doc drift, and opens a clean branch with suggested updates. No prompting. No context setup. No forgetting.

DeepDocs understands both your code and your docs in full context. It updates only what’s necessary and leaves your formatting intact. You can also trigger a full Deep Scan to fix outdated docs across your entire repo in one go. It works with monorepos, external docs repos, integrates easily with popular doc generators like Docusaurus or MkDocs, and fits naturally into your existing GitHub flow.

What I’m most proud of is that it works like CI for documentation. You don’t need to change your habits. Just commit your code and let DeepDocs handle the rest.