AI CodeOps vs Cursor

Cursor and AI CodeOps both let AI agents write code in the cloud and come back with a pull request. They are built for different moments. Cursor is an AI code editor that developers work in all day, with cloud agents and Bugbot alongside it. AI CodeOps is a browser product where agents take a task from start to finish and the change waits at a gate before it ships. This page explains the difference and says when Cursor is the better choice.

Summary, as of October 2026

Cursor is an AI code editor. Its cloud agents run in isolated VMs, can build, test and interact with the changed software, push changes to a separate branch and produce a merge-ready pull request (cloud agents). You can start them from Cursor Desktop, Cursor Web, Cursor for iOS, Slack, Linear, @cursor comments on GitHub or Bitbucket, and the API. Bugbot reviews pull requests on every update by default, and can be set to run only when mentioned or once per pull request (Bugbot).

On October 18, 2026, Cursor's pricing page listed Free ($0), Plus ($8), Premium ($30), Super ($100) and Ultra ($200) per month, and Teams from $30 per user per month. Cloud agents are listed on Premium, Super, Ultra, Teams and Enterprise.

AI CodeOps is a browser-based platform where AI agents plan, build, review and test a code change. The change becomes a pull request only after its quality gates pass and a person approves it. It is free during the open beta. See how AI CodeOps works.

The side-by-side table further down links every fact to its source.

Choose AI CodeOps if…

• You want a gate that holds the change, not a check you have to configure. A pull request opens only when tests pass, the AI review completed and no high or critical finding is open, and the same gate runs again before the console merges (quality gates). Bugbot's status check blocks merges on unresolved findings only when the check is required and its fail-on-unresolved-issues setting is on.
• You want a second person in the loop. A code change needs an approved review from someone other than the person who launched the session, when the team has another approver (approvals and policies).
• Your code is on Gitea or Forgejo. AI CodeOps connects to both, as well as GitHub, GitLab and Bitbucket.
• You want a signed record and capped spend. Each change has a signed evidence pack, and spend caps apply per workspace and per workflow. See cost controls.

Choose Cursor if…

Cursor is the better pick for a lot of teams, for clear reasons.

• Your developers want the AI in their editor. They can also hand work to cloud agents from the desktop app, the web, Slack, Linear or a pull request comment. AI CodeOps has no IDE extension.
• You want an agent in the terminal. The Cursor CLI lets you work with AI agents from your terminal. AI CodeOps has no CLI.
• You use Azure DevOps or Bitbucket Data Center. Bugbot lists both. AI CodeOps connects to neither.
• You run GitHub Enterprise Server. Bugbot lists it, and AI CodeOps doesn't support it.
• You want proof the change works. Cursor's cloud agents return a pull request with screenshots, videos and logs of the change being tested.

Where each fits

Cursor fits the developer's own loop: writing code with AI in the editor, and handing a task to a cloud agent when it's easier to let one run. Bugbot then reviews the pull requests your team opens.

AI CodeOps fits the team's loop: a task goes to a group of agents, which plan it, write it, run your tests in a sandbox and review the diff for correctness and security. A person approves the change before it ships, and the evidence pack records how it got there. It reviews only the changes made in its own sessions, not pull requests people open directly on the Git host.

Using both

Many teams will keep Cursor and add AI CodeOps rather than choose. Developers keep writing code in Cursor. Routine tasks, such as a bug fix, a test or a small feature, go to AI CodeOps, where they wait at the gate for review. AI CodeOps opens ordinary pull requests, so if Bugbot is on for the repository, it reviews those as well.

Moving work to AI CodeOps

1. Keep Cursor in your editor. AI CodeOps works on the repository, not in the IDE, so the two don't overlap.
2. Connect your Git host in AI CodeOps (Settings, then Git Providers) and create a project for one repository.
3. Invite one teammate, so approvals need a second person, and set a workspace budget.
4. Run three or four tasks you would otherwise give a Cursor cloud agent, using the quickstart. Compare the pull requests, the tests that ran, the review findings and the cost per session.
5. Move those tasks over one team at a time. The switch guide lays out a two-week pilot.