Coding & DevFreemium
Devin
Autonomous AI software engineer with cloud and local IDE
- Overview
- Devin is Cognition's autonomous AI software engineer that operates in a cloud sandbox — with a browser, terminal, and code editor — to complete engineering tasks end-to-end from a ticket or prompt, returning a pull request without step-by-step guidance. Cognition's acquisition of Windsurf (rebranded Devin Desktop in June 2026 and listed separately in this directory) expanded the suite to include a local agentic IDE, Devin CLI, and Devin Review for automated PR analysis. It integrates with GitHub, GitLab, Jira, Linear, Slack, Notion, and Sentry, and runs Cognition's own SWE-2 model alongside frontier models from OpenAI, Anthropic, and Google.
- Why it matters
- Devin has moved from a single autonomous-agent product to a full software-engineering platform after acquiring Windsurf and rebranding it Devin Desktop, giving it a footprint in both async cloud execution and the daily IDE workflow. Enterprise adoption — Goldman Sachs, Mercedes-Benz, the US government — signals the category is past proof-of-concept. The April 2026 pricing reset (from a $500 entry to $20) dramatically widened the addressable market, but the real cost scales with agent runtime and seat count, so Teams plans get expensive fast. Watch for SWE-2 quota changes as the promotional free period expires and for whether the ChatGPT token-sharing integration signals deeper OpenAI dependency.
- In practice
- Teams typically start Devin on bounded tasks — writing tests for an existing module, fixing a tracked bug, or scaffolding a new API endpoint — then promote it to longer-horizon work once trust is established. Mercedes-Benz's reported use case (COBOL modernization: 200,000 lines analyzed, an eight-month estimate cut to eight days) illustrates the highest-ROI pattern: high-toil, low-novelty legacy work. The honest limitation is that open-ended or deeply ambiguous tasks still produce unreliable output; Devin works best when the ticket is specific enough that a junior engineer could follow it.
- Best for
- Engineering teams that want to delegate well-scoped, repeatable tasks — bug fixes, test writing, legacy modernization, and boilerplate — to an autonomous agent, and need both a cloud agent and a local IDE under one billing relationship.
- Pricing
- Free tier with limited daily/weekly quota and restricted model access. Pro at $20/seat/month with increased quotas and full frontier model access (OpenAI, Claude, Gemini) plus Devin Cloud. Max at $200/seat/month with significantly higher quotas for heavy users. Teams at $80/month base + $40/month per full developer seat (centralized billing, admin dashboard, priority support). Enterprise is custom. Overages on any paid plan are billed at API list prices; ACUs remain in enterprise order forms only.
Key features
- Runs autonomously in a sandboxed cloud VM with browser, terminal, and editor — handles planning, writing, testing, debugging, and opening PRs
- Devin Desktop (formerly Windsurf): local agentic IDE with Agent Command Center for managing multiple concurrent cloud and local sessions
- Devin Review: automated code review on any GitHub PR, reasoning across files and commit history to flag bugs and suggest fixes
- Cognition SWE-2 in-house model (Medium, High, Max reasoning variants) plus frontier model choice across OpenAI, Anthropic, and Google
- Devin Wiki auto-generates codebase documentation with architecture diagrams; integrates with Jira, Linear, Slack, Notion, and Sentry
Quick answers
- What is Devin?
- Devin is Cognition's autonomous AI software engineer that operates in a cloud sandbox — with a browser, terminal, and code editor — to complete engineering tasks end-to-end from a ticket or prompt, returning a pull request without step-by-step guidance. Cognition's acquisition of Windsurf (rebranded Devin Desktop in June 2026 and listed separately in this directory) expanded the suite to include a local agentic IDE, Devin CLI, and Devin Review for automated PR analysis. It integrates with GitHub, GitLab, Jira, Linear, Slack, Notion, and Sentry, and runs Cognition's own SWE-2 model alongside frontier models from OpenAI, Anthropic, and Google.
- Why does Devin matter?
- Devin has moved from a single autonomous-agent product to a full software-engineering platform after acquiring Windsurf and rebranding it Devin Desktop, giving it a footprint in both async cloud execution and the daily IDE workflow. Enterprise adoption — Goldman Sachs, Mercedes-Benz, the US government — signals the category is past proof-of-concept. The April 2026 pricing reset (from a $500 entry to $20) dramatically widened the addressable market, but the real cost scales with agent runtime and seat count, so Teams plans get expensive fast. Watch for SWE-2 quota changes as the promotional free period expires and for whether the ChatGPT token-sharing integration signals deeper OpenAI dependency.
- What is Devin best for?
- Engineering teams that want to delegate well-scoped, repeatable tasks — bug fixes, test writing, legacy modernization, and boilerplate — to an autonomous agent, and need both a cloud agent and a local IDE under one billing relationship.
- How much does Devin cost?
- Free tier with limited daily/weekly quota and restricted model access. Pro at $20/seat/month with increased quotas and full frontier model access (OpenAI, Claude, Gemini) plus Devin Cloud. Max at $200/seat/month with significantly higher quotas for heavy users. Teams at $80/month base + $40/month per full developer seat (centralized billing, admin dashboard, priority support). Enterprise is custom. Overages on any paid plan are billed at API list prices; ACUs remain in enterprise order forms only.
Seen in recent stories
Where Devin showed up in the last 90 days of KeyNews editions.
Know the terms
Glossary entries that explain what Devin is built on.
Agentic workflow
A multi-step process where an AI agent plans, executes, evaluates, and iterates on tasks with minimal human intervention. Unlike single-turn prompts, agentic workflows involve loops, branching logic, and tool calls that unfold over minutes or hours.
Human-in-the-loop (HITL)
A design pattern where a human reviews, approves, or corrects AI outputs before they take effect in the real world. HITL balances AI automation benefits with human judgment for high-stakes decisions.
Vibe coding
A development approach where a programmer describes what they want in natural language and iterates with an AI coding assistant to produce working software, relying on the AI for implementation details rather than writing code line by line.
AgentOps
The operational discipline of deploying, monitoring, debugging, and managing AI agents in production. AgentOps encompasses observability, cost tracking, failure recovery, human-in-the-loop escalation, and compliance auditing for autonomous AI systems.
Models behind it
The models Devin runs on, offers, or competes with.
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