What keeps documentation in sync with code changes, October 2026

Let me first get something out of the way, because it confused me as well when I started. Generating documentation and keeping documentation correct are two different jobs. A generator takes code and produces a page. It is really good at the first version, and if you have an empty docs folder it is a gift. But it has no idea which existing sentence became wrong last Tuesday. If you run it again you get a new page, not a correction, and the new page has none of the examples, caveats and tone your team added over the last two years.

So whenever I look at a tool now, I don't ask whether it can write documentation. Most of them can, and quite well. I ask whether it can notice that one specific claim on one specific page stopped being true, show me why, and change only that claim. That is the whole game IMO, and everything below is judged on that.

This is the simplest option, and probably the one most engineering teams already use without calling it a tool. You ask Claude Code, Cursor, Codex or Copilot to update the docs as part of the same change, or you run it on a schedule or from CI against the recent commits. A rule in the agent instructions of the repository is often the whole setup.

I like it a lot for docs that live next to the code. The agent sees the diff and the Markdown in the same context, the change goes into the same pull request, and an engineer reviews both together. It costs nothing extra if you already pay for the agent and there is no new vendor to onboard.

Where it falls apart is anything outside the repository. The help center in Notion, the wiki, the runbook in another repo. The agent only updates what it is pointed at, and someone has to remember to point it. There is also no record of which pages were checked and found fine, no rule for which pages may be edited and which must not, and no evidence beyond the pull request itself. And from experience, this kind of habit lives with the engineer who set it up. When they leave, the habit leaves too.

If your docs are repository-first and your readers are engineers, to be honest, this might be all you need. Don't buy anything else before trying it.

If your documentation lives in Notion, the obvious question is why not build the agent inside Notion. Notion's custom agents can run on a schedule or on a Notion event, read what changed in GitHub through a connector, and either edit pages directly or propose line-level suggestions that a person approves. They keep a run log. Workers can also receive external webhooks, and Notion's own guide actually uses a GitHub webhook as the example.

The appeal is that you stay in one place. No second product, the agent can touch any page it has access to, and the suggested-edits flow gives you a review step before anything goes live. If you are automating more than documentation anyway, e.g. status updates and project reports, one agent platform covers all of it.

The catches are less visible until you actually build it. The GitHub connector is pull-only, so a merged pull request or a release does not trigger the agent by itself; you either schedule it or build the webhook chain yourself. Notion has no concept of which pages a repository can make stale, so that logic has to live in the prompt, and somebody on your team has to write it, test it and keep it working. Custom agents also require the Business or Enterprise plan, and runs are metered in credits, which starts to matter when the agent reads a lot of pages to find one wrong sentence.

This suits teams that are already on the right plan and have someone who genuinely wants to own the prompts. If that person exists, it is a fair option. If they don't, it becomes one more automation that worked for a month.

The third approach is to move your documentation to a platform that hosts it and ships its own agent. Mintlify calls itself an intelligent documentation platform with self-updating documentation, and its agent keeps Mintlify-hosted docs current on push or on a schedule. GitBook's agent composes suggested edits for review. ReadMe's AI Writer watches pull requests, finds the affected docs, drafts changes on a review branch and comments on the pull request for a human to approve.

What you get is one vendor owning everything, from the editor to hosting to search to the agent. API reference generation from a specification is native, and the maintenance loop is tight because the platform controls both the source and the output. If you are picking a docs site anyway, the agent comes with it.

What you give up is choice about where the docs live. Pages in Notion, the repository wiki, an internal runbook that is not generated from an API spec, all of these are out of scope. And the migration itself is the real cost: a new editor for the people who write, a new site for the people who read, and a few weeks of nobody being sure which copy is the right one. A related shape is the AI knowledge base. Falconer, for example, pulls from code, Slack, meetings, GitHub and Notion into its own knowledge base, audits it for stale and conflicting content, and proposes updates when the product changes. It is wider than documentation, and the maintained copy lives with the vendor.

If you want a hosted docs site, need API reference generation, and are fine with one vendor owning the experience, this is the right category. Just don't add a separate drift tool on top to do what the platform already does.

The fourth approach keeps your help center where it is, in Intercom, Zendesk, Help Scout or similar, and adds a product that watches what ships and proposes article updates. Pageloop is the clearest example I have found. Its public pages say it watches what your product ships and keeps docs and screenshots accurate, reading GitHub pull requests, GitLab releases, Linear issues, Slack channels and support tickets, then proposing text and screenshot edits in a formatting-aware editor. Every article is versioned and reviewed before it goes live.

I find the screenshot part genuinely clever, and for consumer-facing help it is a real differentiator. The change signals also go beyond code, which matters when a product change is announced in Linear or Slack long before it lands in a release. Review before publish is explicit.

But Notion is not a destination, and neither are repository docs, wikis, runbooks or any engineering prose. If your help center is in Notion, or the same team also needs internal and operational docs kept current, an overlay built for help-center platforms simply does not reach those pages. Pricing is not published on its site either, so you need a call to find out.

If you are a customer-success lead and your source of truth is one of the supported help-center platforms, this is probably your category. Destination fit matters more than any feature checklist here.

And then there is what I am building. Amendary keeps documentation where it already lives, in Notion or in a GitHub docs folder or wiki, maps each page to the repositories that can make it stale, checks those pages when something ships, and drafts a correction with the evidence attached. This is the one section I know from the inside, so take the enthusiasm with a grain of salt and the limitations as accurate.

The reason I built it this way comes from the problem I described at the start. In every team I was in, the docs were spread across audiences: a customer help page in Notion, an on-call runbook in the repository wiki, a product-updates changelog somewhere else. I wanted one loop that covers all of them without asking anyone to migrate. The mapping is explicit, so a page that is not mapped is never touched. Every correction shows the old text, the new text and the release or commit it came from, and any version, path or URL in the draft has to be backed by the change itself, otherwise it is not proposed. Corrections wait in a review queue by default. A paid workspace can let grounded corrections apply on their own, while removals, additions and unsupported values still wait for a person. Applied corrections can be undone for 30 days. Checks and corrections are covered by a flat subscription, and only generating docs from scratch spends credits, because that is the expensive part and I don't want people to think twice before running a check.

What it does not do, and I want to be clear about this: it does not host a docs site, it does not generate API reference from a specification, and it does not publish to Intercom or Zendesk today. It needs someone to map the pages properly; a page mapped to the wrong repository produces wrong or missing corrections. It reads code for evidence but never edits code, so if you want docs changed inside the same product pull request, the coding agent is the better fit. And it finds supported mismatches on mapped pages. It does not promise to catch every stale claim, and I would not trust any tool that does.

It suits B2B SaaS teams shipping from GitHub whose documentation is already spread across Notion and repository docs, serving customers, success, on-call engineers or all three, and who would rather have release-driven checks with evidence and a review step than maintain agent plumbing themselves.

Start with where the documentation lives, not with features. If everything is in the repository and read by engineers, a coding agent is the cheapest answer and may be enough. If it is in Intercom or Zendesk, go for a help-center overlay. If you are about to adopt a docs platform anyway, use its agent and don't buy a second tool. If it is in Notion, or split between Notion and repository docs, you are choosing between building a Notion agent yourself and a drift checker that treats the mapping, the evidence and the review step as the product.

Then ask three things of whatever is left. What triggers a check, and does it match how you actually ship: merged pull requests, landed commits, published releases, or a person remembering? What does a correction look like, and can you see why it was proposed before you accept it? And what happens when the tool is wrong, because it will be wrong at some point: is there a review step, a record of what changed, and a way to undo?

Finally, be honest about who will own it. Every one of these needs someone who cares whether the docs are right. A tool can find the stale sentence and draft the fix. Deciding what the documentation should say, and noticing that a correct page is still unhelpful, stays with your team whichever box you tick. I wish it was otherwise, but after all these years I don't think it ever will be.