It's because HN is in AI meta-psychosis :)
Our experience is very similar except we didn't really have a review process before, and now LLMs find bugs before PRs get merged in main.
We had 5x-100x speedups in some legacy but important pipelines, with no regressions (validated after extensively by humans). It's not that the code was actively bad. It's just only 1-5% people in the local SWE market would be able to write code that runs so fast and efficient and benchmark it correctly.
We found a subtle correctness bug that was in production for half of the decade (both GPT-5 and Claude Opus were able to find it), confirmed by human after.
And we keep finding subtle bugs that have been introduced by humans before (despite the human reviews, the particular domain is just difficult no matter how many docs and comments and tests one writes)