I've been working on a similar agentically engineered regex project called SafeRE:

https://github.com/eaftan/safere

https://eaftan.github.io/safere-intro/

Mine is for Java and is intended to be production grade. The first goal is to guarantee linear-time behavior to prevent ReDoS attacks. My collaborator and I have recently been optimizing it to try to surpass native RE2 in performance.

It turns out optimizations are incredibly well suited for an agentic loop. You've got concrete acceptance criteria (must show a meaninging improvement on a benchmark case, must pass tests). The agent is really, really good at using tools like a profiler and disassembler, better than I am (and I've been doing this for 20 years). It also papers over things that would take me a while to learn, like how the in-incubation Vector (SIMD) API works in Java. I understand the concept but it would take me a while to understand Java's implementation. The agent can just read the docs and go.

The key is creating a good benchmark suite and ensuring the agent doesn't ship optimizations that are too narrow or too focused on the benchmark cases. You also need a really strong test suite to make sure you're not regressing correctness. SafeRE has billions of tests; a subset of several million run on CI, and the others run on-demand.