Devin
Free tierAutonomous AI software engineer — tackles entire GitHub issues end-to-end with minimal supervision.
Paid·Technical·Powered by Cognition·API available
Key strengths
Autonomous end-to-end software engineering (plan, code, test, PR)Runs on its own virtual machines (Windows, Mac, Linux) with browser testingParallel cloud agents for large tasksProactive automations and trigger-based workflowsMulti-model support mixing frontier models for cost efficiencyCode review with bug and vulnerability detection (Devin Review)Integrates with Slack, Teams, GitHub, GitLab, Jira, Linear, PagerDuty
Paid only · from $20 USD/mo
San Francisco, US
Founded 2023
Self-hostable
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Recent changes
- Self-hosting: now available
- Free tier: now available
- Plans updated: Free ($0): light quota, limited models, unlimited inline edits & Tab completions. Pro ($20/mo): increased quotas, frontier models, SWE-2 access, Devin Desktop/CLI, cloud agents. Max ($200/mo): significantly higher quotas. Teams ($80/mo base + $40/mo per full dev seat, up to 200 users). Enterprise: custom pricing.
- Starting price: $500/mo → $20/mo
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Technical Use Cases
- Autonomous PR generation: Assign Devin a GitHub or GitLab issue; it plans, implements, tests, and opens a pull request with no manual coding steps.
- Parallel feature development: Spin up multiple cloud agents simultaneously to tackle independent features or services in parallel, compressing sprint timelines.
- Trigger-based incident response: Connect PagerDuty alerts to Devin so it automatically investigates and begins remediation workflows when incidents fire.
- Automated code review & security scanning: Use Devin Review to detect bugs and vulnerabilities on pull requests or across the codebase as part of a CI gate.
- Cross-platform environment testing: Leverage Devin's Windows, Mac, and Linux VM support to run browser and integration tests across multiple environments without provisioning separate infrastructure.
- Pipeline integration via API: Use the Devin API to embed autonomous coding tasks into existing CI/CD pipelines or internal developer portals.
- Multi-model cost optimization: Route simpler tasks to open-source or lower-cost models while reserving frontier models (Claude, GPT, Gemini) for complex reasoning tasks.
- Legacy codebase migrations: Delegate large-scale refactoring or dependency upgrade tasks to Devin agents running in isolated VMs, reducing risk to production environments.
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