Use an AI Agent to Write and Keep Your README and API Docs Current

Documentation has always failed for the same reason: it's written once, at a moment of enthusiasm, and then the code changes while the words don't. Six months later the README describes an install step that no longer exists and an API that was renamed twice. An AI coding agent attacks both halves of the problem — it can generate accurate first drafts by reading the actual code instead of asking you to remember it, and it can keep those drafts current as part of ordinary feature work. Documentation stops being a project you'll do someday and becomes something that updates in the same commit as the change.

Why agent-written docs start ahead of blank-page docs

The traditional obstacle to documentation is transcription: someone who understands the code must manually pour that understanding into prose. The agent removes most of that step. It reads the source, the config files, and the scripts directly, so its first draft is grounded in what is actually there rather than in anyone's memory of what used to be there. That doesn't make the draft publishable on its own — it still needs your judgment about audience, emphasis, and accuracy — but it converts the task from "write documentation" into "review documentation," which is a dramatically easier ask. The projects that benefit most are precisely the ones nobody documented: inherited codebases and solo projects where the author is also the only person at risk of forgetting how it works.

Generate the README from what the code really does

Ask the agent to produce a README covering the standard sections: what the project is, prerequisites, install, configuration, how to run it locally, how to run tests, and where to look first in the code. The instruction that matters most is to verify rather than reconstruct — have it trace each setup command back to the actual package manifest or script before writing it down, and flag anything it couldn't confirm. Setup instructions that were never executed are the classic README failure, and they're exactly the kind of detail an agent can check mechanically. Then do one real pass yourself: follow the quickstart from scratch on a clean checkout. If step three fails, the README isn't done.

Keep API documentation next to the code

For API references, proximity beats polish. Doc comments on functions and types, kept beside the code they describe, age far better than a separate reference document because a change to a function sits right next to its description in the same diff — hard to update one without noticing the other. Ask the agent to write doc comments as it adds or modifies functions, describing behavior, parameters, and failure modes in plain language. If you want a browsable reference on top of that, have the agent wire up whatever documentation generator fits your language and treat its output as buildable, generated material — never hand-edited, so it can be regenerated without fear. The same co-location discipline is what keeps refactors honest, as described in keeping an AI agent from breaking existing code.

Make doc updates part of the definition of done

The habit that keeps any of this alive is folding documentation into normal work. Add one line to your standard prompt pattern and to whatever review checklist you use: "update all documentation affected by this change." Most agents comply readily once asked; the failure mode is simply that nobody asks, so docs drift silently while features ship. A related trick worth adopting: when the agent finishes a task, occasionally ask it whether any existing docs are now wrong. Agents are good at spotting inconsistencies between code and text, and stale claims get caught this way before they mislead the next reader.

What still needs a human pass

Three things deserve your own eyes before docs go public. Accuracy of claims: agents occasionally describe options or flags that don't exist, especially for fast-moving tools, so verify anything version-sensitive. Secrets: a README drafted from real config files can pick up real credentials in its examples — scrub every sample value, and review security practices around AI-written code if your docs include code samples. And voice: the agent's draft will be competent but generic; two sentences about why the project exists and who it's for are worth more than any amount of auto-generated structure.

The meshcode angle

Doc work parallelizes nicely: drafting, verifying commands, and reviewing for secrets are separate passes over the same repo. In meshcode, a native desktop app for macOS and Windows, each pane runs its own agent session, so one can regenerate the API reference while another proofreads the README against the code. Drive the Claude Code or Codex CLI subscription you already have, or meshcode's metered models billed pay-as-you-go with no monthly fee.

👉 Download meshcode — Mac, Windows