Your AI doc agent is going to draft something wrong. It'll misread a diff, describe an endpoint that doesn't behave the way it guessed, or update the wrong page. The question isn't whether that happens. It's what it costs you when it does.
If a bad draft costs nothing because it never reaches production, you have a working system. If a bad draft means a public doc is now wrong, you don't.
A draft is cheap. A published page isn't.
The reason to route AI-generated changes through a branch is that a draft on a branch has no blast radius. Nobody's integration breaks because of a sentence sitting in a branch waiting for review. You can read it, reject it, or fix it, and the live docs never knew.
This is the whole bet behind branching and reviews: let the agent be wrong somewhere safe. A wrong draft caught in review is the system doing its job, not failing at it. The only genuinely bad outcome is a wrong draft that nobody reads before it merges.
Fix it in the open, not in your head
When you spot a bad draft, the instinct is to quietly correct it and merge. Do the correction in the branch instead, where it's visible. Two reasons:
First, the diff between what the agent wrote and what you shipped is the clearest signal anyone has about where the agent is weak. If you fix it silently, that signal disappears.
Second, the correction is reusable context. An agent that can see how its last draft got edited has something concrete to learn from. Which brings up the part most teams skip.
Feed the correction back
A one-off fix solves today's draft. It doesn't stop the agent from making the same mistake next week. If the agent keeps describing your auth flow wrong, the fix isn't editing each draft. It's giving the agent better grounding so the next draft starts closer to correct.
That usually means improving what the agent reads: the existing docs, the spec, the conventions it's working from. We cover the recurring shapes these mistakes take in agent failure patterns, and the prompting patterns that pull better drafts out of a grounded agent. The pattern across all of them is the same: a correction you make once should change the inputs, not just the output.
How ReadMe puts this together
The GitHub AI Writer drafts on a branch, never straight to production. Reviews and notifications make sure a person sees the draft before it ships, and Enterprise controls let you require that review. So a wrong draft is a non-event: you catch it, correct it where it's visible, and improve what the agent reads next time.
The goal was never an agent that's never wrong. It's a workflow where being wrong is cheap and being right gets easier over time. Start a project or talk to us about Enterprise to set it up.
