Name: Devin
Rating: 6.4 (1 reviews)
Author: Cognition

Our take

Our verdict

6.4/10

Autonomous AI software engineer that writes, debugs, tests, and deploys code end-to-end using a sandboxed browser, terminal, and IDE.

Best for: Engineering teams offloading high volumes of junior-level coding tasks — test writing, vulnerability remediation, repo migrations, and defined ticket work

Overall score6.4/10

Capability7.0

Ease of use6.0

Value for money6.0

Reliability6.0

Support & docs7.0

Pros

Full autonomous development environment — terminal, browser, and IDE accessible in one agent without switching tools
Excels at well-defined junior-level tasks: vulnerability fixes, test writing, migrations, and small ticket completion
67% PR merge rate as of 2025, up from 34% — meaningful real-world output quality improvement
Enterprise-ready with VPC deployment, SAML/OIDC SSO, and centralized billing controls
4x faster problem solving and 83% more tasks per ACU compared to Devin 1.x after the 2.0 overhaul

Cons

Real-world complex-task completion rate remains around 15% without supervision; the 'last 30%' problem persists
ACU-based billing makes monthly costs hard to predict for teams with variable workloads
Gets lost in codebases over 100K lines — prone to modifying wrong files or duplicating existing utilities
Requires well-written, detailed task descriptions; struggles with ambiguous or open-ended requirements

Overview

Devin is an autonomous AI software engineer built by Cognition, a San Francisco startup founded in November 2023 by Scott Wu, Steven Hao, and Walden Yan. Unveiled in March 2024, it became notable as one of the first agents to operate a full development environment — terminal, browser, and IDE — to complete software tasks end-to-end rather than just autocomplete snippets.

Devin 2.0 launched in April 2025, dropping the entry price from $500 to $20 per month and delivering 83% more task completions per compute unit than its predecessor. Billing is based on Agent Compute Units (ACUs), where one ACU equals roughly 15 minutes of active work. By mid-2026, Cognition had raised a Series D at a reported $26 billion valuation, and Goldman Sachs had piloted Devin alongside its 12,000 human developers.

In practice, Devin performs well on junior-level, clearly scoped tasks: fixing vulnerabilities flagged by static analysis, writing test suites, migrating legacy codebases, and churning through backlog tickets. Its 2025 PR merge rate of 67% (up from 34% in 2024) signals genuine production utility. However, independent testing puts complex task completion without supervision at around 15%, and the agent reliably struggles with large codebases, architectural judgment, and ambiguous requirements — areas where senior engineering judgment still dominates.

Key Benefits

Full autonomous loop: Devin researches, writes code, runs tests, fixes failures, and opens pull requests without switching between tools.
Maintenance acceleration: Organizations have reported 20x efficiency gains on vulnerability remediation compared to human developers handling the same workload.
Improving reliability: Consistent year-over-year gains — 4x faster problem-solving and a doubling in resource efficiency since 2024.
Enterprise governance: VPC deployment, SSO, teamspace isolation, and centralized billing make it deployable inside strict security perimeters.

Use Cases

Vulnerability remediation at scale — Devin can process static analysis output from tools like SonarQube and Veracode, fix flagged issues, and submit PRs; one enterprise clocked Devin at 1.5 minutes per fix versus 30 minutes for human developers.
Test suite generation — Given a module and its specs, Devin writes unit and integration tests systematically, freeing engineers for higher-value work.
Legacy codebase migration — Devin handles well-defined modernization tasks such as framework upgrades, dependency migrations, and boilerplate refactors across repositories.
Backlog ticket completion — Teams connect Devin to Jira or Linear and route clearly scoped tickets directly to it, treating it as a non-blocking async engineer on the team.