Atlassian has made its AI-powered Code Reviewer generally available for teams using paid Jira and Teamwork Collection subscriptions, aiming to accelerate software delivery by automating the initial review of pull requests and reducing human bottlenecks.
- AI Code Reviewer reduces review cycle time by 31%
- Works with Jira, Bitbucket Cloud, GitHub (GitLab soon)
- Includes customizable standards checks and quality filters
What happened
Atlassian has launched Code Reviewer as a general availability feature integrated into Jira and Teamwork Collection licenses. The AI tool automatically reviews pull requests on platforms including Bitbucket Cloud and GitHub, with GitLab support planned in the near future. Code Reviewer provides the first pass at code quality, flagging issues and suggesting fixes directly in the pull request interface.
This launch responds to the growing challenges development teams face as AI-assisted code generation increases the volume and size of pull requests. According to Atlassian’s Q3 2026 State of AI Impact report, human reviewers now wait more than twice as long for pull request reviews compared to a year ago while the median pull request size has more than doubled.
Why it matters
Manual code reviews have become a bottleneck in modern software development workflows, especially as teams adopt AI coding agents that accelerate code creation. Code Reviewer addresses this by providing fast, automated feedback grounded in the specific context of linked Jira work items and team standards, helping reviewers focus on complex judgments rather than routine checks.
Early internal use at Atlassian shows the tool reduces median pull request cycle time by 31%, and nearly 40% of its comments directly lead to subsequent code changes. It also includes a quality filtering mechanism to avoid overwhelming teams with low-value comments. This innovation could significantly improve software delivery velocity and maintain code quality at scale.
What to watch next
Atlassian plans to expand Code Reviewer’s platform compatibility with upcoming GitLab support and enhance features like Standards, which lets organizations enforce custom coding rules per repository. Teams adopting the tool are encouraged to enable automatic review to ensure every pull request gets an AI-powered first pass without manual trigger.
The company is emphasizing privacy and control by running reviews in isolated environments and never retaining code post-review. Admins can manage where and when reviews occur, providing flexibility to balance automation and manual oversight. Monitoring adoption and impact metrics will offer insights into how AI-assisted code review reshapes engineering workflows.