Review of Devin by Cognition
Devin is an autonomous AI software engineer by Cognition Labs. You give it a GitHub issue, and it plans the work, navigates the codebase, writes code, runs tests, debugs failures, and opens a pull request. It works in a sandboxed VM with full IDE, browser, and shell access. Pricing: $20/month Core, $100/month Team, custom for Enterprise.
You connect your GitHub repo, give Devin an issue, and it gets to work. It uses Claude 4 Sonnet as its primary model. It can read files, run commands, install dependencies, edit code, and use a browser. When it's done, it opens a PR with a summary of what it changed and why.
Issue: 'Add a /api/unsubscribe endpoint that takes an email and removes it from the Resend audience.' Devin took 14 minutes, wrote the endpoint, added validation, wrote tests, ran the test suite, fixed a bug it found, and opened a PR. The PR was mergeable on first review. Quality: 8/10.
Issue: 'Newsletter form submits but the success message doesn't appear.' Devin took 22 minutes, read the relevant files, identified the bug (a typo in the JS), fixed it, and opened a PR. The fix worked. But Devin also made an unrelated change (renamed a CSS class) that I had to revert. Quality: 6/10 (it does extra stuff sometimes).
Issue: 'Refactor the build script to use ESM imports instead of CommonJS.' Devin took 45 minutes, made the change, ran the build, fixed 3 import errors, and opened a PR. The build worked. But the refactor changed 47 files, and I had to review every one. For a junior dev, this would have taken 2-3 hours. Quality: 7/10 (time saved, but review cost).
Devin is genuinely capable. It can handle multi-file changes, debug errors, and iterate. It remembers context across long sessions. For greenfield features and well-scoped bug fixes, it saves hours. The PR format is great: summary, files changed, tests added.
Devin sometimes makes unrelated changes (renames, formatting, dependency upgrades). You have to review every PR carefully, which negates some of the time savings. It also struggles with ambiguous issues: 'make this faster' is not enough. You need to be specific.
Devin uses an 'ACU' (Agent Compute Unit) system. Core: $20/month, 9 ACUs. Team: $100/month, 40 ACUs. A simple bug fix uses ~1 ACU. A complex refactor uses 5-10 ACUs. Heavy users will burn through Team quickly.
Cursor is an IDE for humans; Devin is an agent. Cursor is better for daily coding; Devin is better for delegating entire tasks. Use Cursor when you want to write code; use Devin when you want code written.
GitHub Copilot Workspace is a similar agent that lives inside GitHub. It's cheaper (free with Copilot) and more integrated with GitHub issues. But it's less capable than Devin for complex tasks. For simple bug fixes, Copilot Workspace is fine. For complex features, Devin is better.
Solo founders with small codebases. Teams with well-tested repos and clear issues. Anyone who wants to delegate greenfield work to an AI. Not for: large legacy codebases, ambiguous requirements, production-critical systems.
Teams that need strict code review (every PR needs to be carefully reviewed anyway, defeating the time savings). Anyone on a tight budget (the cost adds up). Codebases with poor test coverage (Devin relies on tests to verify its work).
Devin is the most capable autonomous coding agent in 2026. It's not perfect, but for the right tasks (well-scoped features, clear bug fixes, refactors with tests), it saves hours. Treat it like a junior dev: review everything, give clear instructions, and don't trust it on critical systems.
|