Overview
Devin is a software engineering agent built by Cognition AI to support engineering teams and developers across end-to-end development tasks. Rather than acting strictly as in-editor autocomplete, it spins up isolated virtual machines with access to a terminal, integrated IDE, and interactive browser, allowing it to investigate repositories, install dependencies, run test suites, validate web interfaces, and open review-ready pull requests.
The platform combines multiple work surfaces tailored to different workflows. Through the cloud web application, teams can delegate tasks in parallel, follow every step in real time, or take direct control of the editor whenever needed. For developers who prefer working locally, the ecosystem includes the Devin CLI in the terminal and Devin Desktop as a full development environment for macOS, Windows, and Linux, with the option to hand off longer-running sessions directly to the cloud.
Beyond writing code, the product incorporates dedicated tools for continuous codebase understanding and review. DeepWiki and Ask Devin generate architectural documentation and answer technical questions prior to implementation, while Devin Review analyzes pull requests, organizes complex diffs, and applies automated fixes in response to review comments or continuous integration failures.
Features and functionality
- Autonomous cloud workspace: runs sessions inside isolated virtual machines equipped with a terminal (Shell), code editor (IDE), and browser (Browser) to write code, execute commands, and test applications end to end.
- Devin CLI and Devin Desktop: lets developers work locally from the command line or inside a dedicated desktop IDE, supporting the /handoff command to delegate time-consuming tasks to cloud sessions.
- Ask Devin and DeepWiki: indexes repositories to map project architecture, generate navigable diagrams and documentation, answer questions about the codebase, and prepare detailed instructions before starting a session.
- Devin Review and automated autofix: structures complex diffs in pull requests, flags bugs or security issues, and can automatically respond to reviewer comments and CI failures.
- Organizational memory and Playbooks: stores recurring team instructions in the Knowledge base, reads repository guidelines from AGENTS.md and SKILL.md files, and reuses standardized Playbooks for frequent tasks.
- Automations and parallel sessions: triggers workflows automatically from GitHub events, Slack messages, tickets, webhooks, or schedules, while coordinating multiple concurrent sessions to clear backlog queues.
Use cases
- Bug resolution and backlog triage: reproduce errors reported in Slack, Linear, or Jira, implement fixes, validate results with tests, and open the corresponding pull request.
- Code migrations and refactoring: upgrade framework versions, convert projects across languages, remove obsolete feature flags, and extract shared libraries across multiple files.
- Automated testing and visual verification: author unit or end-to-end tests and verify application behavior directly inside the session browser, complete with video recordings of the run.
- Continuous pull request review: inspect large code changes with Devin Review and automate adjustments for linting, build errors, or reviewer feedback.
- Technical documentation and onboarding: consult DeepWiki and Ask Devin to understand legacy services, map data flows, and spin up internal tools or prototypes.
How to use
- Create an account at app.devin.ai, connect your version control provider, and configure the repository environment (Blueprint) with dependencies, environment variables, and test commands.
- Before tackling complex tasks, use Ask Devin to explore the codebase, align on the technical approach, and generate a structured prompt with clear completion criteria.
- Start a session from the web interface, Devin CLI, Devin Desktop, or by mentioning @Devin in a Slack, Microsoft Teams, Linear, or Jira thread.
- Monitor progress through the session's terminal, IDE, and browser, review the generated pull request with Devin Review, and verify all tests before merging.
Required experience level
Devin is primarily designed for intermediate and advanced users, including software developers, DevOps engineers, and technical leads. While it accepts natural language instructions, getting reliable results from sessions requires familiarity with Git, pull requests, runtime environment setup, automated testing, and critical code review before shipping changes to production.
Integrations
The platform offers native connections with GitHub, GitLab, Bitbucket, and Azure DevOps for reading repositories and opening pull requests, alongside direct integrations with Slack, Microsoft Teams, Linear, Jira, PagerDuty, and Databricks. The ecosystem also supports the Model Context Protocol (MCP) to connect monitoring tools, databases, documentation, and design platforms, as well as the Devin API to trigger sessions programmatically within CI/CD pipelines.
Plans and pricing
Access is available through a freemium model and paid subscriptions at app.devin.ai. There is a free plan for individual experimentation with limited usage and access to Devin Review and DeepWiki, paid individual tiers (Pro and Max) with recurring allowances covering cloud, CLI, and Desktop sessions, and a Teams plan offering full or flexible seats with shared on-demand credits. For larger organizations, the Enterprise plan provides advanced security options, SSO, access controls, and dedicated deployment via sales contact.
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