Devin

Devin, from Cognition, is positioned as an autonomous AI software engineer rather than an in-editor assistant. You assign it a ticket — a bug fix, a dependency migration, a small feature — through Slack, Linear, or Jira, and it works the task inside its own cloud environment equipped with a browser, a shell, and a code editor. When it finishes, you review a pull request, the same way you would review a junior engineer's work.

The defining feature is fire-and-forget delegation. You do not watch Devin code; you hand it a well-scoped ticket and come back to a PR. Because each Devin runs in its own sandbox, you can run several in parallel on different tickets, which makes it attractive for teams trying to burn down a backlog of repetitive or well-defined work.

Pricing starts around $20/month plus usage-based compute measured in ACUs (Agent Compute Units), so cost scales with how much work you delegate. Devin is at its best on clearly scoped, mechanical tasks — migrations, framework upgrades, repetitive fixes — and weaker on vague or architecturally tricky problems where the right approach is itself the hard part. Costs can climb quickly on complex tasks, so most teams reserve it for the work it does reliably.