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Documentation goes stale by default. Product changes accumulate. Screenshots drift. A feature gets renamed. A workflow that worked in v1 no longer applies in v2. Without deliberate maintenance, the gap between your docs and your product quietly widens until users start noticing — usually through support tickets and lost trust. Maintaining docs well is mostly a process problem, not a writing problem. Mintlify’s tooling, combined with AI used the right way, can automate most of the mechanical work and reduce the manual burden significantly.

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Start with docs-as-code

The foundation of maintainable documentation is treating docs the same way you treat code: version-controlled, reviewed, deployed through a pipeline. If you’re using Mintlify with a GitHub or GitLab repository, you already have this foundation. Documentation changes go through pull requests. Reviewers can catch outdated information before it ships. Preview deployments let you see exactly what a change looks like before it goes live. The key habit to build: documentation changes should ship in the same pull request as the product changes they document. When a feature ships, the docs ship with it. When a feature changes, the docs change in the same PR. This is the single most effective way to prevent drift, and it’s much easier to maintain than a separate docs-update process that runs after the fact.

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Let Mintlify’s agent do the first draft

When product changes outpace the docs team’s capacity, Mintlify’s agent can close the gap. You can configure it to watch your product repository and automatically draft documentation updates when code is merged to main. This doesn’t replace human review — AI-drafted docs need to be checked for accuracy and tone before they ship. But it removes the blank-page problem. Instead of a writer starting from scratch after a feature lands, they’re reviewing and editing a draft that’s already structurally sound.
1

Configure the agent

Set up a GitHub Actions workflow that triggers the Mintlify agent when changes are merged to your product repository’s main branch. See Automate documentation updates for setup instructions.
2

Review the draft PR

The agent opens a pull request in your docs repository with proposed changes. Review for accuracy, tone, and whether the content type is correct for the page being updated.
3

Merge or revise

Approve the changes if they’re accurate, or use the draft as a starting point for a more thorough update.

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Set up automated checks

Mintlify integrates with CI to catch common problems before they reach users:
  • Broken links: Run mint broken-links in CI to catch internal links that lead nowhere — a common byproduct of reorganizing navigation or renaming pages.
  • Style and spelling: Vale checks writing style against rules you define. You can enforce consistent terminology, flag passive voice, or catch product names written incorrectly.
  • Missing metadata: Ensure every page has a title and description before it ships.
These checks don’t require ongoing attention once they’re configured. They run on every pull request and catch problems before users encounter them.

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Know when to update, rewrite, or delete

Not all maintenance is equal. Most changes need a targeted update — fix the thing that changed and move on. But some pages accumulate so many caveats and workarounds that they become harder to follow than a fresh rewrite would be. A page is a candidate for rewriting when:
  • It has more warnings, notes, and “as of version X” qualifiers than actual content
  • The underlying workflow it describes has fundamentally changed
  • Users are frequently confused by it even after incremental improvements
A page is a candidate for deletion when:
  • It documents a feature or workflow that no longer exists
  • The information exists in better form elsewhere
  • It’s receiving very low traffic that can’t be explained by it being a niche reference
Wrong documentation is worse than no documentation. A page that describes a workflow that no longer works costs users more time than a 404 would. If you can’t fix it in the short term, remove it. You can always add it back.

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Use AI to surface what needs attention

AI is useful for maintenance work that doesn’t involve writing. Two practical uses: Audit with AI: Give an AI tool a list of your pages and their last-updated dates, along with a summary of recent product changes. Ask it to flag which pages are likely to need review. It won’t be perfectly accurate, but it’s faster than reading every page manually and gives you a prioritized list to work from. Check for consistency: Ask an AI tool to read through a section of your docs and flag anywhere terminology is inconsistent, or where the same concept is explained differently on different pages. Consistency problems are subtle and humans miss them; AI tools catch them reliably. Neither replaces a human review process — but both make that process faster and more thorough.

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A maintenance rhythm that works

The goal isn’t perfect documentation. It’s documentation that’s accurate enough to be trusted. A lightweight rhythm:
  • With every release: Update docs in the same PR as the feature
  • Monthly: Review Mintlify assistant conversations and search analytics for gaps
  • Quarterly: Audit your highest-traffic pages for accuracy and freshness
  • Annually: Assess whether your overall structure still reflects how users actually use your product
Documentation is never finished. But with the right process in place, it stays close enough to the truth that users can rely on it — and that’s what matters. That’s the end of the Structure docs that scale course. You’ve covered the decisions that determine whether your documentation holds up over time: who you’re writing for, how to categorize content, how to design navigation around user goals, and how to keep everything accurate as your product changes. The principles here work together — and the AI tools woven throughout will help you apply them consistently at scale.