Agentcode

Use case

AI for developers that clears your backlog

Lead developers and engineering managers have a backlog of well-scoped tickets that never quite reach the top of anyone's day. Agentcode picks them up and ships them as pull requests you review.

In short

Agentcode is an autonomous AI coding agent for engineering teams. You describe a task or assign a ticket, and the agent plans the change, edits your codebase, runs your existing test suite, and opens a pull request on your GitHub or GitLab repo. It is review-first: it never merges on its own, so a human always approves the change before it lands. It works on your real repository and CI, and it never trains on your code.

The problem

Your backlog of small, well-scoped tickets keeps growing because every senior engineer is busy on the hard stuff.

How Agentcode helps

Point Agentcode at the tickets you have already scoped and let it work through them in parallel. For each task it plans the approach, makes the edits across the relevant files, runs your test suite, and opens a pull request with a clear description of what changed and why. Your team reviews the diff the same way you review any colleague's PR, requests changes if needed, and merges when it is right. Nothing ships without a human approval, so you clear the backlog without losing control of what lands on your main branch.

See it run

From task to pull request

Agent Run

Pick a task

Plan

  • planning

Files changed

Test run

0 failed

Pull request

Open

You review and merge. Agentcode never merges on its own.

Ship more, review what matters