Docs that stay current
because the code writes them
Documentation is accurate on launch day and wrong six months later, because nobody updates a wiki page when a function signature changes three sprints later. We build an agent that reads the actual code and recent changes, and keeps the docs matching reality instead of matching the day they were written.
The process today
Documentation rot is one of the most consistently reported frustrations in engineering surveys: a new hire follows the onboarding wiki, hits a step that no longer matches the actual setup, and spends an afternoon in Slack asking someone who already knows. The common pattern is that docs get written carefully once, at launch or during a big feature push, and then nobody owns keeping them current, because updating documentation competes for the same time as writing the next feature and loses every time.
The cost is not abstract. Teams that track support ticket causes often find a meaningful share traces back to documentation that technically exists but describes an old version of the product. Internally, the same gap shows up as repeated questions in a team’s chat that a correct wiki page would have answered, and as onboarding that takes longer than it should because the written process and the real process diverged months ago.
What the agent does
Reads the actual code and recent merges, not just a static snapshot, so API documentation reflects the endpoints, parameters and response shapes that actually exist right now.
Flags wiki and internal doc pages for update the moment the code or process they describe changes, instead of waiting for someone to notice the page is wrong during an unrelated search.
Drafts onboarding guide corrections when setup steps, dependencies or environment variables change, so a new hire’s first week is not spent debugging a wiki page instead of the actual product.
Fills in missing code comments and docstrings for functions that shipped without them, using the function’s actual logic and call sites to write an accurate description rather than a placeholder.
Regenerates architecture diagrams when the underlying system changes meaningfully, keeping a visual reference current without someone manually redrawing boxes and arrows every quarter.
Reports which doc pages have drifted from the code or process they describe, ranked by how long ago they last matched, so a technical writer can prioritize instead of scanning the whole wiki.
What stays with humans
The agent drafts and flags, it does not publish. A technical writer or engineer reviews every drafted change before it replaces a live page, especially anything involving security guidance, compliance language, or instructions that touch production systems. Decisions about documentation structure, what belongs in a public API reference versus an internal wiki, stay with the people who own that structure.
Guards
A review period where drafts land in a pull request or a staging doc instead of overwriting a live page, so your team checks tone and accuracy against real pages first. Every draft logs the code change or ticket that triggered it, so a reviewer can verify the claim rather than trusting it blindly. Rate limits prevent a large refactor from generating an overwhelming queue of doc updates at once, and a kill switch pulls the agent off any repo or doc space instantly.
Price and timeline
| Package | Price | Best for |
|---|---|---|
| Single automation | from $600 | One repo and one docs platform, kept in sync with the actual code and process |
| Department package | from $2,500 | Documentation plus code review, test generation and release notes for the same codebase |
3 to 7 days, most of it spent learning your existing doc structure and tone so the first drafts already read like your team wrote them.
Related
Works naturally with code review and release notes, since a documented change and a changelog entry often come from the same pull request. Teams building API integration glue usually need documentation kept current for the integrations themselves. Part of automation of everything digital and built the way we build AI agents for our own products. We keep this discipline on our own products, including the AI media buyer for Meta Ads and the secure messenger built on the Signal protocol.
Tell us which repo and docs platform you want kept current and we will send back a fixed price and a plan for the first week: get in touch.
Tired of doing this by hand? We can take the whole routine off your team, not just this step: Routine takeover, from $400 →
FAQ
How much does an AI documentation agent cost?
A single-repo agent keeping API docs and one wiki in sync starts from $600. A department package covering documentation alongside code review, test generation and release notes starts from $2,500, depending on how many repos and doc platforms are in scope.
How long does it take to go live?
3 to 7 days: connecting to your repo and documentation platform, learning your existing doc structure and tone, and a short review period where drafts are checked against real pages before the agent is trusted to flag updates on its own.
Which tools does it connect to?
GitHub, GitLab and Bitbucket for code, Notion, Confluence, GitBook or your own docs site for publishing, OpenAPI or Swagger specs for API documentation, and Claude for turning a diff into readable explanation rather than a mechanical restatement of the code.
What if the agent documents something incorrectly?
It drafts into a review queue, never publishes directly, and every draft links back to the code or ticket it was generated from so a reviewer can verify a claim before it goes live. Technical reviewers check accuracy before anything replaces the existing page.
Is our codebase and internal wiki safe?
The agent reads only the repositories and docs platforms you connect it to, under your own provider's permissions, and does not retain your code or internal documentation outside the drafting session.