Technical Writer's Living Documentation System

Category: Academy · Stage: Implementation

By Max Beech, Head of Content

Updated 12 October 2025

Documentation goes stale the moment you publish it. An engineer ships a breaking change, forgets to update the docs, and support tickets multiply. Users complain that "the instructions don't work," eroding trust in your entire documentation set.

The problem isn't lazy engineers. It's documentation systems that rely on human memory instead of automated checks. If updating docs requires remembering to do so, it won't happen consistently.

TL;DR

• Link documentation to code versioning so changes trigger review prompts
• Use automated tests that fail when docs diverge from implementation
• Build lightweight contribution workflows so engineers can fix docs without context-switching
• Track documentation health in Chaos and schedule regular audits

Jump to: 1. Docs-as-code approach | 2. Automated staleness detection | 3. Contribution workflows | 4. Maintenance schedules

Docs-as-code approach

Store docs in version control

Keep documentation in the same repository as your code, not a separate wiki or Google Drive. This means:

• Docs are versioned alongside code releases
• Changes to code and docs happen in the same Pull Request
• Documentation review is part of code review

Use formats that version control handles well: Markdown, MDX, AsciiDoc. Avoid binary formats (Word, PDFs) that don't diff cleanly.

Branch per feature

When an engineer creates a feature branch (feature/new-auth-flow), the corresponding documentation lives in that branch. The PR review checklist includes "Documentation updated?" before merging.

Deployment sync

When you deploy version 2.3, the docs site should automatically show 2.3 documentation. Use tools like Docusaurus, GitBook, or Read the Docs that support versioned docs out of the box.

Automated staleness detection

Code-to-docs linking

For API documentation, generate it directly from code:

• OpenAPI/Swagger: Auto-generate API reference from spec files
• JSDoc/TSDoc: Extract function descriptions from inline code comments
• GraphQL: Generate schema docs from GraphQL definitions

When the code changes, docs regenerate automatically. No manual sync required.

Example code tests

If your docs include code examples, test them in your CI pipeline. A failing test means the example is broken and docs need updating.

Example: Your docs show how to authenticate:

curl -H "Authorization: Bearer TOKEN" https://api.example.com/users

Add a test that runs this exact command. If your API changes to require a different header, the test fails, alerting you to update the docs.

Link checking

Broken links erode credibility. Run automated link checkers (e.g., linkinator, markdown-link-check) in CI. Flag dead links before merging. Set up weekly scheduled checks for external links that might rot over time.

Last-updated metadata

Add a "last updated" date to every page. After six months with no updates, flag the page for review. Tools like Docusaurus can automate this based on Git history.

Contribution workflows

In-app "suggest an edit" links

Every documentation page should have a visible "Edit this page" link that takes the user directly to the source file on GitHub. This reduces friction: users can fix typos or clarify confusing passages without emailing you.

Lightweight PR templates

When someone opens a docs PR, provide a simple checklist:

• [ ] Checked spelling and grammar
• [ ] Tested code examples (if applicable)
• [ ] Updated related pages (if applicable)

Don't require engineers to become technical writers. Accept imperfect contributions and polish them yourself. It's faster than writing from scratch.

Doc champions in engineering

Identify one engineer per team who cares about documentation. They review docs PRs and advocate for keeping them updated. This distributes the workload and ensures domain expertise.

Maintenance schedules

Quarterly documentation audits

Block half a day each quarter to review:

• Pages with zero updates in 6+ months
• Support tickets mentioning "docs are wrong"
• Analytics showing high bounce rates (users land and leave immediately)

Delete outdated pages rather than leaving them to confuse users. Redirect to relevant replacements or archive clearly.

Release note automation

When code merges to main, extract commit messages (following Conventional Commits format) and auto-generate release notes. Tools like semantic-release or release-drafter handle this. Engineers write meaningful commit messages, and release notes populate automatically.

User feedback loops

Add a simple feedback widget to each page: "Was this helpful? Yes / No." If "No" responses exceed 20%, investigate. Often a small clarification fixes confusion.

How does documentation maintenance integrate with Chaos?

Set recurring prompts: "Quarterly docs audit—check staleness and support feedback." When a new feature ships, add a task: "Update API docs for new authentication flow." If a user reports a docs issue, capture it immediately: "Fix timezone handling example in Getting Started guide."

For team collaboration, see our Research Ops Repository Workflow for strategies on maintaining shared knowledge. If you're coordinating with engineering, the AI Daily Standup Automation shows how to surface docs tasks without disrupting flow.

What if engineers still won't update docs?

Make it easier than not doing it:

• Auto-generate where possible (API specs, type definitions)
• Accept rough drafts and polish them yourself
• Celebrate good documentation in team channels to build culture
• Make docs PRs part of the definition of "done" for features

If none of that works, documentation debt becomes technical debt. Surface the cost: "We spent 40 support hours this month answering questions already in docs that users couldn't find or trust."

Key takeaways

• Store docs in code repositories so updates happen alongside feature development
• Use automated tests and link checkers to catch staleness before users do
• Reduce contribution friction with in-app edit links and lightweight PR templates
• Schedule quarterly audits to prune outdated pages and prioritise high-impact fixes

Summary

Documentation rots because updating it requires memory and effort at inconvenient times. A docs-as-code approach ties updates to code releases, automated tests catch drift, lightweight workflows welcome contributions, and scheduled audits prevent long-term decay. With Chaos tracking maintenance cycles, your documentation stays trustworthy.

Next steps

1. Move documentation into your code repository if it's currently in a separate system
2. Add automated tests for code examples and link checking to your CI pipeline
3. Add an "Edit this page" link to every documentation page
4. Schedule quarterly docs audits in Chaos and assign an owner for each review

About the author

Max Beech helps technical teams build documentation systems that don't require heroic maintenance. Every workflow is tested with real engineering orgs.

Review note: Framework validated with three developer tools companies (10-100 person eng teams) in September 2025.