AI CodeOps docs: quickstart, Git setup, gates, API

Go from sign-up to your first AI change that passed its quality gates and opened a pull request: account, Git, project, session, approval. About ten minutes.

Follow one AI CodeOps session from task to merged pull request: agents plan and build, your tests run in a sandbox, AI review flags issues, a person approves.

The building blocks of AI CodeOps: organizations, workspaces, projects, agents, workflows, sessions, findings, gates, approvals, changes and deployments.

What the AI CodeOps open beta includes: free use, the monthly AI token allowance, your own model key, how your code and data are handled, and what comes after.

Which Git hosts AI CodeOps works with (GitHub, GitLab, Bitbucket, Gitea and Forgejo), how each one connects, and what the platform does in your repositories.

Connect a GitHub.com account to AI CodeOps with OAuth or a personal access token, the scopes it needs, and what the platform does with your repositories.

Connect GitLab.com or a self-managed GitLab instance to AI CodeOps with OAuth or a personal access token, and see how merge requests are opened for you.

Connect a Bitbucket Cloud account to AI CodeOps with OAuth so sessions can push branches and open pull requests, plus the limits of token-based connections.

Connect your own Gitea server to AI CodeOps with a personal access token: the instance URL, the token scopes it needs, and how pull requests are opened for you.

Connect a Forgejo server, such as Codeberg or your own instance, to AI CodeOps with a personal access token, and see what the platform does with your repos.

Create a project in AI CodeOps: link a Git repository or start from scratch, set the default branch and test command, and see what a project tracks over time.

The OAuth scopes and token permissions AI CodeOps asks for on GitHub, GitLab, Bitbucket, Gitea and Forgejo, what each is used for, and how to revoke access.

The AI agents that run in an AI CodeOps session and the 16 built-in workflows that order them, from Plan, Build, Review & Test to Incident Response.

Choose how AI CodeOps sessions get a model: the platform's Economy, Standard and Premium tiers or Auto within your plan's allowance, or your own provider key.

Start an AI session in AI CodeOps: describe the task, pick a project and workflow, watch the agents work live, review the diff, and open a pull request.

The 16 built-in AI CodeOps workflows and their steps, plus how to start one, schedule it, re-run it, cancel it, and build on a finished session with follow-ups.

How AI CodeOps decides whether a change can ship: test results, the AI findings review, approvals, and the release gate check your CI can call.

Set what AI sessions may do with workspace policy rules (allow, ask, deny) and how human approvals work: who can approve, expiry, and rejections.

How AI CodeOps reviews a change with several agents: review steps, a findings pass over the real diff, severity and triage, and the human approval that follows.

How AI CodeOps handles security findings, SBOMs per project (CycloneDX and SPDX), license checks in the release gate, sandboxed terminals and encrypted secrets.

Run the Dependency Auditor agent on your project, see what it reads and reports, and how its findings land in the review that gates the pull request.

Write workspace policy rules for AI sessions: the seven actions, allow, ask and deny, resource globs, trust postures, log-only mode, and a worked example.

Download a signed record of how one change was made (task, models, approvals, findings, tests, delivery) and verify it in the browser or offline.

How AI CodeOps hands a merged change to your deploy pipeline: the quality gate before merge, deploy webhooks, policy rules per environment and deploy records.

What rollback means in AI CodeOps: you roll back in your own deploy pipeline, then mark the deployment rolled back so history and failure rate stay accurate.

Cap AI spend in AI CodeOps with a workspace budget and per-workflow caps, see cost per session and per step, and read the Usage page's allowance and charts.

See what AI CodeOps spends: cost per session and per agent step, cost by agent across sessions, the Usage page's allowance, daily cost and call history.

Invite people to an AI CodeOps workspace, choose built-in roles from owner to viewer, create custom roles on Enterprise, and require two-factor sign-in.

Every built-in AI CodeOps role and what it can do: who starts sessions, who approves changes, who edits policies, plus custom roles and how roles are assigned.

What the AI CodeOps audit log records, how to read and filter it under Measure → Audit Log, who can see it, and how long entries are kept on each plan.

Set up SAML 2.0 or OpenID Connect sign-in for AI CodeOps on the Enterprise plan: verify your domain, create a connection, configure your IdP and activate it.

How long AI CodeOps keeps sessions, audit records, delivery logs and backups, how to export your account data, how deletion works, and how your code is used.

What the AI CodeOps Enterprise plan adds: SSO with SAML or OIDC, custom roles, audit history kept for the life of your organization, and self-hosting.

An overview of running AI CodeOps on your own Kubernetes cluster, an Enterprise option on request: what it involves, what it needs, and how to get started.

What you can call programmatically today: the release gate check for CI with a workspace API key, and the public evidence pack keys. The API is limited in beta.

Send AI CodeOps events to Slack, Discord, Teams or your own HTTPS endpoint, verify signed payloads, and call your deploy pipeline when a change merges.

Connect remote MCP servers so AI CodeOps agents can call their tools: add a server, keep its headers encrypted, and limit tools per agent and by policy.

Connect Claude Code, Cursor or any MCP client to AI CodeOps: start sessions, read findings, check the release gate and fetch evidence packs from your editor.

Fixes for common AI CodeOps problems: Git connections, sessions that stop on allowance or budget, pull requests that won't open, missing pages and sign-in.

Short answers about AI CodeOps: what it does, what it costs in the open beta, which Git hosts and models it supports, and how it handles your code and data.

Get help with AI CodeOps: ask the in-console Help assistant, open a support ticket, email the team, check the status page, or report a security issue.