AI coding tools can produce a striking burst of productivity — but the initial surge may not last. A Carnegie Mellon study of public repositories adopting Cursor found a three- to five-fold increase in lines added during the first month, with the gains dissipating after roughly two months. The study, which used SonarQube (Sonar’s core platform) to measure code quality, also found that static analysis warnings rose by 30% and code complexity by 41%. The short-term velocity boost therefore comes with a persistent increase in technical debt. Tom Howlett , Sonar ’s Director of AI Engineering...

Source: The New Stack