AI Coding Agents: Real ROI Numbers from Production Teams

Anonymized data from 12 engineering teams using Cursor, Cline, and Devin in production.

By Creative Genius · May 12, 2026 · 7 min read

The "10× engineer with AI" narrative is mostly marketing. The real numbers are still impressive — and more useful for budgeting. Here's anonymized data from 12 engineering teams (5 to 80 engineers) using Cursor, Cline, or Devin in production over the last six months.

The headline numbers

Median productivity gain: 22% on greenfield projects, 8% on legacy codebases.
Bug introduction rate: roughly comparable to human-only baseline, slightly higher on multi-file refactors.
Time-to-first-PR for new hires: down 40%. The biggest single ROI we measured.
Code review time: up 12% — reviewers now look harder, because the author isn't always the human.

Where AI coding wins consistently

Writing first drafts of tests against existing code.
Boilerplate (CRUD endpoints, form components, migration scripts).
Translating between frameworks (Express → Fastify, React → Solid).
Stack-trace debugging on isolated bugs.
Explaining unfamiliar code or library APIs.

Where it consistently fails

Large refactors that cross module boundaries.
Debugging async race conditions or non-determinism.
Anything requiring runtime state inspection.
Architectural decisions that need product context the model can't see.
Reading large unfamiliar codebases to find the right place to make a change.

The cost side of ROI

Cursor at $20/user/month + Anthropic API costs averaged ~$60/eng/month in our sample. At $150K/yr fully loaded eng cost, a 22% productivity gain on greenfield is worth $33K/eng/year. ROI is decisively positive on greenfield, marginal on pure legacy maintenance.

What predicted high ROI in our sample

Senior engineers who knew when to override the agent.
Codebases with strong test coverage (the agent gets fast feedback).
Teams with explicit "AI use" norms in code review (when to require human-written commits, when AI is fine).
Greenfield work over legacy.

Bottom line

AI coding agents are a real productivity unlock — modest on aggregate, significant on specific tasks. Buy the seats, measure the impact, and don't let your team confuse it with magic.