Loop Engineering: Optimizing Code Generation and Verification
Summary
The article presents Loop Engineering as a practical framework to optimize AI-assisted software development, focusing on transforming generated candidates into verifiable outcomes. It outlines the four-loop structure—terminal evaluation, inner loop, and learning loop—plus methods to convert obligations into checks, design conformance contracts, and measure the cost and effectiveness of detectors and repairs. It also discusses risks in verification bottlenecks and provides guidance through examples and a path for becoming more efficient in the build and review processes.