AI sped up coding. Sonar instills confidence with verification.
A Carnegie Mellon study found that AI coding tools produced a three- to five-fold increase in lines of code during the first month, but gains plateaued after two months. Meanwhile, static analysis warnings rose 30% and code complexity increased 41%, indicating persistent technical debt. Sonar highlights that manual code review processes cannot keep pace with AI-generated code volumes, creating bottlenecks and quality concerns when developers rely on the same review methods for exponentially more code.
Key points
- AI coding tools show initial 3-5x productivity surge followed by plateau
- Technical debt rises: 30% more warnings, 41% more complexity
- Manual code review processes become a bottleneck at scale
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