AI CodeOps for Bitbucket

AI CodeOps works with Bitbucket Cloud workspaces. You connect Bitbucket once, then describe a change in the browser. Agents plan it, write it, review it and run the project's tests, and the result arrives in Bitbucket as a pull request that has already passed your quality gates.

What the integration does

• Repositories: Develop → Repositories lists the repositories the connected account can see, with their branches, files and pull requests.
• Projects: a project points at one repository. Sessions in that project clone it, write the change and test it in a sandbox. See projects.
• Branches and pull requests: when a change is approved and passes the release gate, AI CodeOps pushes a branch named codeops/run-<id> and opens a pull request into the project's default branch. Commits are authored as "AI CodeOps".
• Merging: a pull request the console opened can be merged from the console, and the release gate runs again first. You can also merge it in Bitbucket as usual.

AI CodeOps doesn't install webhooks, post commit statuses or comment on your pull requests. It never pushes to your default branch directly.

How to connect

Connect with Bitbucket OAuth. Bitbucket lists the permissions on its consent screen; AI CodeOps uses them to read your account and repositories, push branches, and create and merge pull requests. OAuth tokens are refreshed automatically before they expire.

Token connections are limited: the token is sent as a Bearer token, so app passwords and API tokens that need your username alongside them don't work. OAuth is the reliable way to connect.

The full steps, scopes and error messages are in Connect Bitbucket. Tokens are encrypted at rest (AES-256-GCM) and never written into a repository's Git configuration. To remove access, disconnect in AI CodeOps or revoke the token in Bitbucket.

Why teams use it with Bitbucket

If your team keeps planning in Jira and code in Bitbucket, AI CodeOps sits between the two: describe the change, let the agents do the work, and review the pull request that comes out the other side.

Every change carries its history with it: which model wrote it, what the reviewers found, which tests ran and who approved it. That history is kept as a signed evidence pack you can hand to an auditor. Spend is visible per session and capped per workspace, so an agent can't run up a bill unseen. See cost controls.

Getting started

1. Create a free account: AI CodeOps is in open beta and runs in your browser.
2. Connect Bitbucket from Configure → Settings → Git Providers.
3. Create a project from a repository and run a first session. The quickstart walks through it.

AI CodeOps also works with the other Git hosts, so a team that uses more than one can run them all from one workspace.

For partners

AI CodeOps is a browser-based platform where AI agents plan, write, review and test code changes and open them as pull requests on Bitbucket. Changes merge only after tests, an AI review and the required approvals pass, and each one keeps a signed record of how it was made. Free during its open beta: https://aicodeops.dev/integrations/bitbucket