Cognition 宣布 Devin 正式开放，每月 500 美元起

Today we’re making Devin generally available starting at $500 a month for engineering teams, which includes:

No seat limits; Access to Devin’s Slack integration, IDE extension, and API; Onboarding session & support from the Cognition engineering team

All engineering teams can now start working with Devin at app.devin.ai.

Where Devin Shines

While Devin can be an all-purpose tool, we recommend starting with:

Small frontend bugs and edge cases - tag Devin in Slack threads; Creating first-draft PRs for backlog tasks - assign Devin tasks from your todo list at the start of your day; Making targeted code refactors - use the Devin IDE extension (for VSCode and forks) to point Devin to parts of the code you want edited or upgraded

Devin has helped teams with everything from building integrations to migrating and maintaining documentation. Devin is versatile, but works best when you:

Give Devin tasks that you know how to do yourself; Tell Devin how to test or check its own work; Keep sessions under ~3 hours and break down large tasks; Share detailed requirements upfront; Invest in coaching Devin by providing feedback in chat and accepting suggested Knowledge, or adding your own Knowledge manually

Working with Devin

Slack is the primary interface for spinning up Devin sessions, so you can quickly tag @devin to offload smaller tasks and fix bugs when they’re reported.

Try asking Devin to do the first pass on the next 3rd party integration, refactor, or codebase question you have. Devin messages you when it’s done, so you can review Devin’s PR whenever convenient. Devin responds automatically to your Github PR comments.

Hand off async work to Devin directly from your IDE with ⌘ G. The Devin extension (Beta Feature available for VScode and forks) allows you to checkout Devin’s PRs and review and accept Devin’s code directly in your IDE.

Contributing to Open Source Repositories

To showcase Devin in action, we’re sharing sessions where Devin resolves issues on a few of our favorite open-source repositories. Devin often needs guidance but we share these examples to show how we use Devin to speed our own workflows.

Anthropic MCP In this session, Devin identifies the cause of a user-reported issue. We liked how it read the MCP spec in the browser to understand “capability negotiation” and tested its changes end-to-end in the browser. The changes weren’t perfect, so the maintainers gave some feedback on the PR which we addressed with a second Devin session.

Zod This PR adds a new feature to the popular library Zod. Devin planned collaboratively with the user, implemented the feature across multiple files and wrote tests – we were very impressed! There was a merge conflict which we manually resolved because Devin tends to struggle with that.

Google

A user of the Go Github client wished it propagated response objects even on HTTP errors. These small chores are annoying for human engineers because testing is often more effort than the fix itself. Devin required a few iterations to get it right and we manually cleaned up a few stray edits using the VS Code extension. The biggest timesaver here was Devin writing and running the unit tests.

Llama Index

Devin fixes a bug where the implementation of the Anthropic tokenizer followed the protocol incorrectly. It found the correct fix first try and wrote a unit test too. A PR comment from the maintainer requested a small stylistic change which we fixed manually.

Karpathy’s nanoGPT This change is just a one-liner. But we wouldn’t trust this change without testing – which Devin did nicely by writing an ad-hoc testing script.

Hire Devin

You can start working with Devin today at app.devin.ai.

For more information about Devin Enterprise, reach out to our Sales team here.