Devin

What is Devin?

Devin is an autonomous cloud software engineer built by Cognition. Unlike an in-editor copilot, Devin runs asynchronously in its own cloud environment — you assign it a task in Slack, Linear, the web app or via API and it plans, writes code, runs tests and opens a pull request for review, largely unattended. It is positioned for delegated engineering work — migrations, refactors, bug fixes, CI failures and documentation — and can be scaled to a fleet of parallel Devins on large multi-repo projects. Cognition’s acquisition of Windsurf finished its rebrand into Devin Desktop in June 2026. Cognition itself raised a $1B+ Series D at a $25B pre-money ($26B post-money) valuation in May 2026 — up from $10.2B eight months earlier — reporting a $492M annualized revenue run-rate and naming enterprise customers including Citi, Mercedes-Benz, Goldman Sachs, Dell and Santander.

What does Devin do?

You describe an engineering task in natural language and Devin executes it end-to-end in a sandboxed cloud workspace: it reads the repository, forms a plan, edits code across files, runs a real shell and browser, executes tests, fixes its own failures and finally raises a pull request with a summary for a human to review and merge. It keeps a live session you can watch and steer, and maintains persistent knowledge of a codebase through Devin Wiki and Ask Devin. Work is triggered from Slack, Linear, the web app, the Devin IDE, the Devin CLI or the Devin API, so it can be wired into CI, scheduled maintenance and incident response rather than driven only by hand. Because Devin runs its own machines, several Devins can work in parallel on independent tickets, and Cognition markets orchestrating “a team of Devins” on large migrations across many repositories. It runs on frontier models (Claude, GPT, Gemini) plus Cognition’s own SWE models — including SWE-1.7 (July 2026), tuned for strong cost-performance on real coding tasks rather than a raw benchmark crown — and integrates with GitHub, CI tooling and observability systems so it can act on real signals like a failing build or a Sentry error.

Key features

• Async cloud sessions: Runs each task on its own cloud VM with a real shell and browser, working unattended until it opens a PR.
• PR-first workflow: Delivers work as a reviewable pull request with a summary, keeping a human in the loop for the merge.
• Fleet of parallel Devins: Spin up multiple Devins to tackle independent tickets or a large multi-repo migration in parallel.
• Devin Wiki & Ask Devin: Builds persistent, queryable knowledge of your codebase to ground its work and answer questions.
• SWE-1.7 model: Cognition’s own coding model (shipped 2026-07-08), tuned for a strong cost-to-performance ratio — well below frontier-model cost per task, though it trails true frontier models on the hardest benchmarks.

What are Devin's use cases?

• Large-scale migrations: Delegate a framework or language migration across many repositories to a coordinated team of Devins.
• Backlog + CI toil: Assign routine bug fixes, dependency bumps and failing-CI investigations from Linear or Slack and review the PRs it returns.
• Incident response: Wire Devin to Sentry or Datadog so it can triage an error and open a fix PR straight from the alert.

What does Devin integrate with?

• GitHub & CI pipelines
• Slack & Microsoft Teams
• Linear, Jira & Notion
• Sentry & Datadog
• Devin API
• Devin CLI
• Model Context Protocol (MCP) — MCP Marketplace, connects as a client to external MCP servers

Why use Devin?

• Truly asynchronous — you delegate a ticket and get a reviewed PR, freeing engineers from routine work.
• Runs its own cloud machines, so many Devins can work in parallel on independent tasks.
• Deep tool surface — Slack, Linear, GitHub, an IDE, a CLI and a public API make it easy to wire into existing workflows.
• Backed by a $1B+ Series D at a $26B valuation (May 2026) and a $492M revenue run-rate, with named enterprise deployments (Citi, Mercedes-Benz, Goldman Sachs, Dell, Santander) — a real signal of production trust at scale.

Pros & cons

Devin pricing

• FreeFree
• Pro$20 / /month
• Max$200 / /month
• Teams$80 / /month + $40/seat
• EnterpriseCustom

See current pricing on devin.ai ↗Compare Devin alternatives →

Devin review

Devin is the most complete attempt at a genuinely autonomous software engineer: it works asynchronously on its own cloud machine, opens real pull requests, and can be scaled to a fleet on large migrations. It is now also one of the best-capitalized bets in the category — a $1B+ Series D at a $26B valuation (May 2026), $492M in annualized revenue, and named enterprise deployments at Citi, Mercedes-Benz, Goldman Sachs, Dell and Santander back up the pitch with real production usage, not just funding hype. Its July 2026 SWE-1.7 model is a genuine cost-performance play — cheap per task, but Cognition’s own numbers put it behind Claude Opus 4.8 and GPT-5.5 on the hardest benchmarks, so treat it as the efficient default rather than the ceiling. The honest catch on autonomy itself remains: independent reviewers still find it stalls or over-engineers on ambiguous tasks, so its PRs are a draft for review, not a finished merge, and billing can drift once on-demand credits kick in on long sessions. Pick Devin if your bottleneck is well-scoped, delegable engineering work you can review as PRs, or you want a vendor with real enterprise-scale traction behind it; skip it if you want a fast interactive copilot in your own editor, where Cursor or Devin Desktop fit better, or you need frontier-level output on the single hardest tasks without switching models.

The category’s boldest bet on full autonomy — now backed by a $26B valuation and real enterprise scale, but still treat its PRs as drafts, not done work.

Frequently asked questions