So far, the best way I’ve found to improve code quality from LLMs that you’ve already produced is to read the output, throw it away, and hand-write it from scratch, usually with a totally different structure.

This scales about as well as it sounds like it would.

Multi-model review does a decent job identifying things they’re outright wrong. The resulting code still doesn’t feel elegant writ large.

If you want good output, it seems that iterating on the output is inferior to providing better input inclusive of code examples. And by the time you’ve made all the decisions that go into that, something like ponytail is superfluous.

(All that said, I have ponytail installed in most harnesses.)