Pull request

A pull request asks for a set of changes on one branch of a repository to be merged into another, usually the main version. It gathers the changed material, an explanation, review comments and the results of automated checks in one place, so the work can be reviewed before it becomes part of the shared source. GitLab calls the same thing a merge request.

Most pull requests follow the same sequence. Someone creates a branch, a separate line of work, and makes their changes there. They open a pull request describing what changed and why. The platform shows a diff, the line-by-line difference between the branch and the main version. Reviewers comment on specific lines, suggest edits or request changes, and the author updates the branch in response. Automated checks run on each update. When the required approvals and checks are in place, someone merges the branch and the change becomes part of the main version.

Why it matters for content

Most content teams already review changes, usually through tracked changes or suggestion mode in Word and Google Docs. That handles the edit itself well, showing what changed and gathering comments in place. The weaker point is what happens next. The approved text is copied into a CMS, sometimes picking up fresh edits on the way, and the record of who agreed to what stays in a document that rarely gets opened again.

A pull request closes that gap, because the change that was reviewed is the change that gets published. The discussion and approval stay attached to the content after it goes live, so anyone asking later why a page changed can find out. Related edits can travel together: a new product name across forty pages is reviewed as one change, published at once and reversed at once if needed. Automated checks can test links, alt text and house style on every update, and a preview shows the page as readers will see it.

Docs-as-code teams got there first, since their documentation already lived beside the product code, but the approach suits any content where accuracy matters, from product pages and policies to interface copy. Git-based content management systems such as Decap CMS open and merge pull requests behind ordinary save and publish buttons, so writers needn’t see a branch. Where content stays in a conventional CMS, the habits still transfer: a stated reason for each change, a clear approver and a record that outlasts the conversation.

How AI changes the picture

AI can suggest style changes, summarise a large change and point reviewers towards likely risks before a person reads it. Link and accessibility tests may use ordinary automation instead. Neither an AI review nor a passing test establishes that the whole change is sound.

Automated review should support accountability rather than replace it. Models can miss context or object to deliberate wording. A named person still decides whether the content is accurate, appropriate and safe to publish.

AI-generated changes also need provenance. When an agent opens a pull request, reviewers should see the source, instructions and scope, rather than judging polished output without knowing how it arose.