A new approach called lf-lean demonstrates that verified software engineering can scale without requiring human review of every code change. Researchers achieved a 350x speedup by translating 1,276 statements from Rocq to Lean using AI, requiring only ~2 person-days versus an estimated 2.75 person-years manually. This breakthrough addresses the fundamental scaling problem in AI-assisted programming.

Traditional code review becomes a bottleneck as AI generates more code faster than humans can review it. The team's solution uses task-level specification generators that define correctness once for entire classes of transformations like translation, optimization, and refactoring. Instead of reviewing each code change individually, the system automatically verifies semantic equivalence across all instances, scaling human oversight from linear to constant effort.

The implications are significant for software verification, long considered too expensive for practical development. As AI coding capabilities advance, having machines verify correctness automatically becomes necessary rather than optional. The rocq-dove prototype environment automatically generates correctness specifications from source code, allowing frontier AI models to autonomously produce verified translations. With 97% of statements completed autonomously and only 6 extreme-difficulty cases requiring manual intervention, verified software engineering is catching up to unverified approaches faster than expected.