Cursor provides a real increase in productivity, especially at the beginning.
But those who combine AI with:
- tests
- code reviews
- quality gates
- statistical analysis
How they analysed?
Scientists from Carnegie Mellon studied 807 repositories, where developers switched to Cursor
(via configs like.cursorrules) and compared them with 1380 control projects - before and after implementation.
The Difference-in-differences method: they compared same repositories *before/after*, plus controlled trends by months.
🚀 What happened to "code velocity"
Code Velocity = commits + lines of code.
- in first month - a jump of 3–5x in lines
- on average after implementation - +1.84x to the velocity
AI really speeds up work - and this is measurable, not just a feeling.
🧩 But there are side effects
Quality was assessed via SonarQube
(reliability, maintainability, security, duplicates, cognitive complexity).
- static warnings - +30%
- code complexity - +41%
- as a result, the velocity starts to decline over time
AI helps to write more - but not always better.
benefit the most. AI agents are accelerators, but quality still requires an engineer.
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