Technical documentation is one of the most undervalued forms of engineering communication. Everyone agrees it matters. Almost nobody prioritizes it. I’ve watched this pattern repeat at every company I’ve worked with, and the failure mode is always the same: docs rot because nobody owns them.
AI won’t fix that problem. But it can remove the excuse.
The Drafting Problem
The hardest part of writing docs is getting started. A blank page plus a busy engineer usually means no documentation. AI is genuinely good at solving this specific problem. Feed it the code structure, recent PRs, and changelogs, and you can get a usable first draft in minutes instead of hours.
That draft will be wrong in places. It will miss context. It will occasionally hallucinate an API parameter that doesn’t exist. That’s fine. A wrong draft you can edit is still faster than a correct document nobody writes.
Where It Falls Apart
The moment you treat AI output as finished documentation, you’ve created something worse than no documentation at all. Wrong docs train people to distrust all docs. I’ve seen this happen: a team auto-generates reference pages, skips review, and six months later nobody believes anything in the docs. They go straight to the source code. The docs become decoration.
The fix is dead simple: AI drafts, humans review, same PR as the code change. No separate workflow. No “we’ll update the docs later.” If the docs don’t land in the same review cycle as the code, they’ll drift. This isn’t a tooling problem. It’s a discipline problem.
The Search Use Case
The other place AI helps is doc search. A retrieval-backed answer system that points users to the right section – with citations – is genuinely useful. The key constraint: it should refuse to answer when it can’t find supporting material. “I don’t know, but here’s the closest section” is a better answer than a confident fabrication.
I’ve been setting this up across a few projects and the pattern holds. Grounded search with citations works. Generative answers without grounding don’t.
What I Would Actually Do
If I were starting a docs workflow today:
- Generate first drafts from code context. Edit for accuracy and tone before merging.
- Block releases when critical docs are stale. Make it a CI check if you have to.
- Keep docs in the repo. Same review, same merge, same ownership.
- Add retrieval-backed search with citation links. Refuse when unsupported.
None of this is complicated. The tooling exists. The gap is always ownership and review discipline, not technology. AI makes the drafting faster. It doesn’t make the caring automatic.