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Coding Agents🟡Low Code
T

Devin

AI software engineer that codes, fixes bugs, and ships features autonomously. Builds full applications end-to-end with minimal supervision.

Starting atFrom $20/month
Visit Devin →
💡

In Plain English

AI software engineer that codes, fixes bugs, and ships features autonomously.

OverviewFeaturesPricingUse CasesLimitationsFAQ

Overview

Devin is the world's first fully autonomous AI software engineer, built by Cognition. Unlike traditional code assistants like GitHub Copilot or Cursor that suggest completions inline, Devin independently plans, writes, debugs, and deploys entire software projects using its own sandboxed development environment complete with shell, code editor, and web browser.

The platform operates as a parallel cloud SWE (Software Engineering) agent. You assign tasks through Slack, Jira, Linear, or its web interface, and Devin works autonomously—breaking down requirements, writing code across multiple files, running tests, and submitting pull requests. It handles complex multi-step engineering workflows that would typically require hours of developer time. Cognition's founding team includes 10 International Olympiad in Informatics (IOI) gold medalists and builders from organizations like Cursor, Scale AI, Google DeepMind, Waymo, and Nuro, bringing deep expertise in both competitive problem-solving and applied AI.

Devin uses Agent Compute Units (ACUs) to measure work. One ACU roughly covers a single discrete task like fixing a bug, building a small website, or restoring a commit. ACUs reflect actual compute usage—idle time doesn't consume units, making the pricing model fair for tasks that require thought but not continuous execution. Recent updates have introduced the ability to schedule and manage multiple Devin agents simultaneously, autofix code review comments from pull requests, and modernize legacy systems including COBOL codebases at Fortune 500 companies. The platform is also available for government use cases through Cognition for Government.

The sandboxed environment provides a full development workspace with shell access, VS Code-style editor, and browser for testing, ensuring Devin can't accidentally modify production systems while working on tasks. Teams report 3-5x speedup on routine engineering tasks like framework migrations, batch bug fixes, CRUD application building, and MVP prototyping.

Compared to open-source alternatives like Aider or SWE-Agent, Devin offers a more polished, managed experience with enterprise features like SSO, hybrid deployment, and parallel agent execution. However, at $500/user/month for the Team plan, it represents a significant investment that's best suited for engineering teams with substantial backlogs of well-defined tasks.

Output quality varies on novel or architecturally complex work, and human review remains essential for production-critical code. The ACU-based pricing can escalate on complex tasks that require extended planning and debugging cycles.

🎨

Vibe Coding Friendly?

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Difficulty:intermediate

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Editorial Review

Devin is the first AI software engineer that works autonomously on full development tasks. Core plan starts at $20/month with limited compute credits. Compared to Copilot ($19/user/month) which assists coding, Devin attempts entire tasks independently. Strong on bug fixes and migrations, weaker on ambiguous feature work. Worth testing at $20/month for repetitive engineering tasks.

Key Features

Autonomous Sandboxed Development Environment+

Devin operates in a fully isolated cloud workspace equipped with a shell, VS Code-style code editor, and web browser. This allows it to independently write code, install dependencies, run tests, and even browse documentation without risking changes to production systems. The sandbox replicates a real developer workstation, enabling Devin to handle the full development lifecycle from planning to pull request.

Multi-Agent Scheduling and Management+

Teams can schedule and manage multiple Devin agents working in parallel on different tasks simultaneously. This allows engineering teams to distribute their backlog across several agents, dramatically increasing throughput for independent tasks. The scheduling system lets you queue work and have Devin agents pick up tasks automatically, functioning like an elastic pool of junior developers.

Automated Code Review Autofix+

Devin can automatically address code review feedback left on pull requests, closing the review loop without requiring the original developer to context-switch back to the task. When reviewers leave comments requesting changes, Devin interprets the feedback, makes the appropriate modifications, and updates the PR. This reduces the back-and-forth cycles that often slow down code review processes.

Workflow Integration via Slack, Jira, and Linear+

Rather than requiring a separate interface, Devin accepts task assignments directly through tools teams already use—Slack messages, Jira tickets, or Linear issues. This lowers adoption friction and lets engineering managers assign work to Devin using the same workflow they use for human developers. Completed work is delivered as GitHub pull requests ready for review.

SWE-1.6 Foundation Model+

Devin is powered by Cognition's proprietary SWE-1.6 model, purpose-built for software engineering tasks including code generation, debugging, and multi-step planning. The model is continuously improved by Cognition's research team and is specifically optimized for agentic coding workflows rather than general-purpose language understanding. Updates to the model improve both code quality and the user experience of interacting with Devin.

Pricing Plans

Core

$20/month

    Team

    $500/month per user

      Enterprise

      Custom pricing

        See Full Pricing →Free vs Paid →Is it worth it? →

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        Best Use Cases

        🎯

        Migrating large codebases between frameworks or library versions (e.g., React class components to hooks, Python 2 to 3) where changes are repetitive but span hundreds of files

        ⚡

        Clearing engineering backlogs of well-scoped bug fixes and small feature requests by running multiple Devin agents in parallel on independent tickets

        🔧

        Building CRUD applications and internal tools from specifications, where Devin can scaffold the full stack including API, database schema, and frontend

        🚀

        Modernizing legacy systems including COBOL codebases at enterprise scale, translating legacy business logic into modern languages and architectures

        💡

        Rapid MVP prototyping where speed matters more than architectural perfection—getting a working demo deployed in hours instead of days

        🔄

        Automating code review feedback loops by having Devin auto-fix reviewer comments on pull requests, reducing back-and-forth cycles between developers

        Limitations & What It Can't Do

        We believe in transparent reviews. Here's what Devin doesn't handle well:

        • ⚠Cannot replace senior engineering judgment for architectural decisions, system design, or trade-off analysis—works best on well-defined, scoped tasks
        • ⚠ACU consumption is opaque and difficult to predict in advance, making budget planning challenging for teams with variable workloads
        • ⚠Sandboxed environment means Devin cannot directly access production systems, proprietary internal tools, or services behind corporate firewalls without enterprise hybrid deployment
        • ⚠Performance degrades on tasks requiring deep understanding of business domain context that isn't captured in the codebase or documentation
        • ⚠All generated code requires human review before merging—Devin may introduce subtle bugs, security vulnerabilities, or suboptimal patterns that pass automated tests

        Pros & Cons

        ✓ Pros

        • ✓Truly autonomous coding agent that plans, writes, debugs, and deploys independently without constant prompting
        • ✓Full sandboxed development environment with shell, code editor, and web browser prevents accidental production changes
        • ✓Handles complex multi-file, multi-step engineering workflows end-to-end including test execution and PR submission
        • ✓Deep integrations with existing workflows via Slack, Jira, Linear, and GitHub for task assignment and delivery
        • ✓Can schedule and manage multiple parallel Devin agents to tackle backlogs simultaneously
        • ✓ACU-based pricing only charges for actual compute—idle thinking time doesn't consume units

        ✗ Cons

        • ✗Expensive entry point at $500/user/month for Team plan, making it cost-prohibitive for small teams or individual developers
        • ✗ACU consumption is unpredictable on complex tasks requiring extended debugging cycles, leading to variable costs
        • ✗Output quality degrades on novel architectural decisions or highly creative engineering work requiring deep domain expertise
        • ✗Human code review remains essential for production-critical code—Devin is not a replacement for senior engineering judgment
        • ✗Limited transparency into reasoning process makes it difficult to understand why Devin chose a particular implementation approach

        Frequently Asked Questions

        What is an ACU and how does Devin's pricing actually work?+

        An Agent Compute Unit (ACU) is Devin's consumption-based billing metric. One ACU roughly corresponds to a single discrete task such as fixing a bug, building a small website, or implementing a specific feature. The key advantage of ACU pricing is that you're only charged for active compute—if Devin is idle or waiting, it doesn't consume units. However, complex tasks that require extensive planning, debugging, and iteration can consume multiple ACUs, so costs can vary significantly depending on task complexity. The Core plan starts at $20/month with included ACUs, while the Team plan at $500/user/month provides higher limits.

        How does Devin differ from code completion tools like GitHub Copilot or Cursor?+

        Devin operates as a fully autonomous software engineering agent rather than a code suggestion tool. While GitHub Copilot and Cursor provide inline code completions as you type, Devin works independently in its own sandboxed environment—you assign it a task and it plans the approach, writes code across multiple files, runs tests, debugs issues, and submits pull requests without requiring your continuous involvement. Think of Copilot as an assistant sitting next to you, while Devin is more like a junior developer working on a separate branch who comes back with a completed pull request for your review.

        What types of tasks is Devin best and worst at handling?+

        Devin excels at well-defined, routine engineering tasks: framework migrations, batch bug fixes, CRUD application building, boilerplate generation, test writing, and MVP prototyping. It performs well when requirements are clear and the task follows established patterns. Devin struggles with tasks requiring novel architectural decisions, ambiguous requirements, deep domain-specific knowledge, or creative problem-solving that demands understanding business context beyond the codebase. It also has difficulty with highly interconnected systems where changes ripple unpredictably across the codebase.

        Can Devin work with my existing development tools and CI/CD pipelines?+

        Yes, Devin integrates with common engineering workflows. You can assign tasks through Slack, Jira, or Linear, and Devin delivers completed work as GitHub pull requests. Its sandboxed environment includes shell access for running build tools, test suites, and other command-line utilities your project depends on. Devin can interact with your existing codebase context and repository structure. For enterprise customers, Cognition offers hybrid deployment options and SSO integration to fit within existing security and access control requirements.

        Is Devin available for government and regulated industry use cases?+

        Yes, Cognition launched Cognition for Government in early 2026, specifically designed to meet the compliance and security requirements of government agencies and regulated industries. This offering provides additional security controls and deployment options beyond the standard enterprise tier. Cognition also announced expansion into the Japanese market in partnership with Takumi Masai in April 2026, indicating growing international availability. For specific compliance certifications and deployment details, contacting Cognition's sales team directly is recommended.
        🦞

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        What's New in 2026

        •SWE-1.6 model released (April 2026) — latest foundation model improving code quality and agent UX
        •Devin 2.2 launched (February 2026) — major platform update with enhanced capabilities
        •Devin can now schedule and manage multiple Devin agents (March 2026) — enabling parallel task execution and automated orchestration
        •Autofix for code review comments (February 2026) — Devin automatically addresses reviewer feedback on pull requests
        •Cognition for Government launched (February 2026) — dedicated offering for government and regulated industry use cases
        •COBOL modernization support (April 2026) — Devin deployed at Fortune 500 companies to modernize legacy COBOL systems
        •Japan market launch (April 2026) — partnership with Takumi Masai for Japanese market expansion

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        Quick Info

        Category

        Coding Agents

        Website

        cognition.ai
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