Docs as code, also called documentation as code, means writing, reviewing, and publishing documentation through a software-development-style workflow: plain-text source files, version control, peer review, and automated builds.
That workflow can make documentation easier to review and publish, but the people responsible for documentation still have to define how updates move through it. Someone has to decide how updates get submitted, who reviews them, and who fixes the build when publishing breaks.
Why Docs-as-Code Workflows Break Down
A docs-as-code setup can look like it is working. The files are versioned, the site builds, and the team creates pull requests. The real problem shows up when the product changes and nobody knows how the documentation should get updated. A small documentation change then turns into a stalled pull request.
A common pattern looks like this: a writer updates an authentication guide and opens a pull request, but the update stops there. Nobody knows who should review the technical change. Then a dependency update breaks the build, and the person who understood the deployment settings has moved to another project. The files are in Git and the publishing setup is in place, but the update is already waiting on someone to own the next step.
The review step is usually where that missing ownership becomes visible. A team launches the site, documents the commands, and tells contributors to open a pull request. Then routine updates raise questions the rollout never answered: which changes need technical review, who checks terminology and task flow, how support should flag a missing article, and who can publish an urgent correction. When nobody has clear answers, contributors start inventing their own process. Reviews become inconsistent, and updates take longer to publish.
Git Becomes a Contributor Barrier
Git can become the next barrier, especially for writers and occasional contributors. Engineers often learn how to work with branches, diffs, merge conflicts, and rebasing gradually through product work. A writer may have to learn how to create a branch, read a diff, resolve a merge conflict, and understand a rebase during the first week of a documentation migration. Support, product, and marketing contributors may have even less reason to work in the repository, so the process can feel bigger than the correction they need to make.
Tom Johnson has written about this same problem as part of the docs-as-code “broken promise”: Git gives writers more control over source files and review history, but the knowledge required to use it can pull time away from research and content maintenance. That tradeoff becomes harder to justify when an occasional contributor only needs to report a small documentation change.
The Publishing Pipeline Needs an Owner
Git friction is not the only maintenance burden. The publishing setup needs attention too. Dependencies need updates, generator upgrades can break templates, and access changes can block reviewers. When the build fails, someone has to know how the pieces fit together well enough to fix it. Teams often plan for the launch and leave that ongoing maintenance without a named owner.
When nobody owns that maintenance, the documentation starts to fall behind. Product changes continue while reviews slow down and the pipeline receives less attention. Support answers questions the docs should already cover, and readers lose confidence in what they find. At that point, the publishing problem has become part of a broader technical documentation maintenance problem.
By then, the publishing setup can look like the problem. Replacing the static site generator may help if the tool no longer fits the team, but the same delays can follow the work into a new setup. The better starting point is the workflow: how a change enters the documentation, who reviews it, what blocks publication, and who fixes the build when it fails. Where the work stops shows whether the team has a publishing problem, a review problem, or an ownership problem.
Signs Your Docs-as-Code Setup Is Getting Stuck
The warning signs usually show up in daily documentation work before the build fails completely. Routine updates wait for review, small fixes take longer than they should, and contributors stop sending changes because the process feels too complicated. Look for patterns like these:
- Writers spend more time troubleshooting builds and merge conflicts than researching or updating documentation.
- Documentation updates trail product changes even though the workflow was supposed to keep them closer together.
- Support, product, or marketing contributors stop sending corrections because the Git workflow creates too much friction.
- Pull requests sit because nobody clearly owns technical review, editorial review, or publication.
- Dependencies, permissions, or deployment settings go unmaintained because the original setup team has moved on.
One sign may point to a temporary workload problem. Several signs at once usually point to a workflow problem. The setup may be missing a contribution path, a review owner, a publishing owner, or enough maintenance time to keep routine updates moving.
Recognize several of these symptoms?
I’ll look at where documentation updates slow down and whether the issue is contribution, review, publishing, or build ownership.
What a Working Docs-as-Code Setup Actually Needs
A working docs-as-code setup starts by giving contributors a realistic way to send changes. Authors who work in the docs every week may use branches and pull requests. Occasional contributors may need a form, an issue template, or another intake path. Support, product, and marketing teams should be able to report a correction without learning the full Git workflow first.
After a change enters the workflow, contributors need to know who reviews it. Technical accuracy, editorial quality, and publication approval are separate decisions, even when one person handles more than one of them. When that change comes in through a pull request, the review moves faster when each decision has a clear owner and the next handoff is obvious.
Reviewing pull requests gets easier when the team agrees on authoring standards before every pull request turns into the same discussion. Teams need shared rules for page structure, file location, links, code samples, metadata, and reusable components. The rules should answer repeat questions without becoming another large document that nobody maintains.
The build and publishing setup needs an owner too. Failed builds, dependency notices, access problems, and generator changes can block publication for days when nobody is watching them. Documentation still needs its own owner because a successful deployment does not tell you whether the guidance is accurate or current.
The right fix depends on where the work stops. Unclear review handoffs may need named reviewers and approval rules. If occasional contributors keep getting blocked by Git, the team may need to route those updates through the intake path described earlier. Repeated build failures usually point to publishing ownership. A team that cannot maintain the build and publishing setup may need a simpler publishing model.
The Docs-as-Code Toolchain
Once the team knows what the build and publishing setup needs to support, the next question is which tools should support that setup. A docs-as-code toolchain is the set of tools that turns documentation source files into a reviewed and published site. That definition lines up with the Write the Docs guide, a practitioner resource for documentation teams, which describes docs as code around issue tracking, version control, reviews, automated tests, and builds.
In practice, a typical docs-as-code toolchain combines a text editor, a lightweight source format, Git-based version control, a static site generator, and automated build and deployment. GitHub Actions or GitLab CI can run checks and builds.
GitHub Pages and GitLab Pages are common publishing options for teams already working in those platforms, and both support custom domains. Cloudflare Pages and Netlify can also publish the generated site. In my experience, documentation often lives in a separate repository from product code, although I’ve worked with both models. Repository structure depends on the organization and should support the way contributors, reviews, and releases already work.
The toolchain explains how source files become a published site. The documentation still has to help someone complete a task. For example, API teams see the same gap when a build works perfectly but a developer still cannot make a first successful API call without help. A strong pipeline supports the documentation work; it cannot replace the review and ownership behind that work.
When Docs as Code Is the Wrong Choice
Docs as code works best when the people responsible for documentation can maintain a Git-based review and publishing process. Some teams cannot support that workflow without slowing down routine updates. For those teams, the overhead can outweigh the value.
A documentation team made up mostly of nontechnical contributors may spend too much time on repository mechanics. Localization can add another layer because translation teams often depend on assignment queues, side-by-side language views, terminology controls, and translation memory. A traditional content management system may serve those contributors and localization workflows more directly.
Another example is customer support and subject matter experts who need to contribute often. Direct Git use can make small corrections harder than they need to be. A repository workflow can still work when those contributors have a simple way to report changes and someone owns how that input becomes a reviewed update. When every correction requires Git, useful knowledge may stop reaching the documentation team.
Docs as code may also be the wrong choice when nobody can maintain the generator, automation, permissions, templates, and deployment settings over time. A managed platform or simpler publishing process may be a better choice in that situation.
A publishing setup only works if the team can keep using and maintaining it. The right choice depends on the organization, the contributors, the review requirements, and the update frequency. A simpler setup can be the better option when a sophisticated pipeline makes routine updates harder.
I Help Fix Documentation Workflows
I help teams find the workflow problem behind stalled documentation updates. Sometimes that means a docs-as-code setup that looked good at launch but became hard to maintain. Other times, a team has not adopted docs as code yet, but updates still get stuck in unclear intake, review, publishing, or ownership steps. I look at how updates enter the documentation, who reviews them, what blocks publication, and who is responsible when the process breaks.
Docs as Code FAQs
What is an example of docs as code?
A team might write product documentation in Markdown, store it in a GitHub or GitLab repository, review changes through pull requests, and publish the site through an automated build. The source files, review history, and deployment configuration remain versioned alongside the rest of the documentation workflow.
Is docs as code only for developers?
No. Docs as code describes the workflow used to manage and publish documentation. Writers can create and maintain the content while developers or subject matter experts review technical accuracy. Other contributors can provide updates through an intake path when direct Git participation creates unnecessary friction.
What tools are used in a docs-as-code workflow?
A typical setup combines a text editor, a lightweight markup format, Git-based version control, a static site generator, and an automated build service. Automation tools can run checks and builds, while a publishing service turns the source files into a live site. The toolchain still needs clear contribution paths, review ownership, and publishing maintenance.
Why do engineering teams use docs as code?
Engineering teams often adopt docs as code because the workflow makes documentation changes visible in the same review systems they already use for software. Version history, pull requests, automated checks, and repeatable builds can make changes easier to trace. Those benefits depend on a review process and pipeline ownership the team can maintain.
How is docs as code different from a traditional CMS?
Docs as code uses version-controlled source files, pull requests, and automated builds. A traditional CMS usually gives contributors a browser-based editor and built-in publishing controls. Teams with frequent nontechnical contributors or heavy localization may find a CMS easier to operate.
Do documentation and product code need to share a repository?
No. Documentation and product code can live in the same repository or in separate repositories. The better choice depends on the organization, who contributes to the documentation, how product changes trigger updates, and who maintains the build and publishing setup.
Documentation updates getting stuck?
I’ll look at what is holding up updates, whether that is contribution, review, publishing, build maintenance, or the way the team is expected to use Git.