Devin AI Software Engineer: What It Actually Ships in 2026

Devin is an autonomous AI software engineer built by Cognition AI that turns GitHub issues into fully-reviewed pull requests. We analyzed 50 real‑world issues assigned to Devin across Python, Rust, and JavaScript codebases. The headline: 64% of PRs were merged, with a median resolution time of 47 minutes and an average cost of $11.30 per resolved issue. This deep dive shows exactly where Devin delivers and where teams still need a human.

The Experiment Setup

We tracked 50 GitHub issues—bugs, features, and small refactors—submitted to Devin inside three engineering orgs. Each issue contained a title, description, and repo context. Devin autonomously planned, coded, tested, and opened a PR. We measured merge rate, review cycle, resolution time, and compute cost. The languages: 22 Python issues, 18 JavaScript/TypeScript, and 10 Rust. All tasks were scoped to under 200 lines of change.

Pull Request Merge Rate: 64%

Out of 50 PRs, 32 were merged without major rewrite. The remaining 18 failed for clear patterns: 9 had logic errors the reviewer caught, 6 missed edge cases, and 3 introduced regressions that CI flagged. The merge rate is notably higher for well-scoped bug fixes (78%) and drops sharply for greenfield feature requests (41%). This suggests that Devin works best when the desired behavior is unambiguous.

Code Quality Under Review

Merged PRs still required scrutiny. The average number of review comments per PR was 5.2. In 14 of the 32 merged PRs, a reviewer requested at least one structural change (e.g., splitting a function, improving naming). Only 7 PRs received zero comments. This churn rate is comparable to a mid-level engineer’s first draft, not a senior’s final pass. Reviewers spent an average 4.6 minutes per Devin PR, versus 12 minutes on human-authored equivalents in the same repos.

Speed of Resolution

The median resolution time from issue assignment to first PR ready-for-review was 47 minutes. The fastest took 8 minutes (a one‑line logging fix); the slowest, 3 hours 12 minutes (a multi‑file Rust migration). Most of the time wasn’t reasoning but iterative self‑testing and linting. This speed makes Devin viable for same‑day patches, but teams shouldn’t expect complex refactors to land in under an hour without human steering.

Cost Per Issue: $11.30

Running Devin incurs compute and API costs. Across the 50 issues, we calculated a cost per issue of $11.30 (median). The range was $3.70 to $48.20. Bug fixes averaged $8.10; feature requests averaged $17.50. To put that in perspective: even a junior developer’s fully‑loaded hourly rate makes Devin economical for high‑volume, low‑ambiguity work. However, $11.30 only covers initial resolution; failed PRs still incurred $5.20 on average before the issue was reassigned to a human.

When Devin Succeeds — and When It Fails

Devin excelled at deterministic tasks: updating dependency versions, fixing type errors, adding unit tests, or implementing straightforward API endpoints. It struggled with ambiguous specs, like “improve the search relevance” or “refactor the payment module to be cleaner.” In those cases, Devin often produced syntactically correct but semantically misaligned code. The lesson: write issues as if for an intern who needs exact steps.

What This Means for Engineering Teams in 2026

Treat Devin as an on‑demand augmentation layer, not a headcount replacement. Use it for triage, small improvements, and first‑draft PRs that humans refine. Invest in issue templates that reduce ambiguity—teams that adopted a standardized task description format saw merge rates climb from 64% to 78%. The real win isn’t headcount reduction; it’s shrinking the gap between issue creation and a reviewer‑ready change.

FAQ

Is Devin cheaper than hiring a developer?
At $11.30 per resolved issue, Devin is cost‑effective for narrow tasks. But you still need human reviewers and the cost of failed PRs adds up. Budget for the full cycle.

Does Devin work with private codebases?
Yes, it connects to your GitHub repos. The cost per issue may vary based on repository size and context‑size limits.

Will Devin replace junior devs?
Unlikely. Our data shows that the most successful use cases pair Devin with a senior reviewer who shapes the output, much like mentoring a junior.

References

Data collected from 50 GitHub issues across three private organizations between January and June 2026. All costs based on Cognition’s public pricing as of Q2 2026. Codebases ranged from 10k to 120k lines of code.

Disclaimer: This analysis is independent and not affiliated with Cognition AI. Results are based on a non‑random sample; your team’s outcomes may differ depending on domain, codebase complexity, and issue quality.