AI code generation is fast, but verification is the new bottleneck
Loop Engineering: Optimizing Code Generation and Verification
AI-assisted coding can boost output by 958% and PRs by 86%, but review times have grown 91% and bugs per developer 9%. Bradley Gibbs outlines loop engineering: a conformance contract, independent checks, and enforced stopping rules to preserve human judgment. The goal is to make 'done' checkable and human review easier, not just to generate more code faster.
A passing suite can therefore mean the tests were rewritten to agree with the code, which is why the evaluator’s checks and expected results need to sit outside the builder’s authority to change.
- duhhhhh1212
https://www.pangram.com/history/664f8cc4-cfcb-40f4-8c81-e468...
Don't waste your time. (s)Looped!!
- bradleygibbs
Author here. This is a detailed (8,000+ word, plus 2 companion pieces) walk-through of building loops for code generation and verification, complete with artifacts and detailed explanations to allow you to implement any of these techniques.
We walk through building:
- an evaluation contract, evaluator and stopping conditions to minimize bugs
- establishing an environment and priming AI to produce production-quality tests and code
- detecting and correcting common AI failure modes
- building a learning loop to monitor and improve all phases.
I'd love to get your feedback!
Brad