Somewhat related, the experiment ongoing at https://www.ecdsa.fail/ is fascinating: it's a competitive, leaderboard-style research challenge trying to optimise a quantum circuit for breaking ECDSA (specifically the elliptic-curve point addition in Shor's algorithm). It quickly surpassed a result announced by Google researchers last month. Now it's showing a 40% gain over Google's result.

TDLR: No.

Their centaur idea[1] is interesting and quite straightforward. It should be fairly easy to implement using a coding agent for the LLM and the ask-and-tell interface in pycma[2].

[1]: https://github.com/ferreirafabio/autoresearch-automl/blob/ma...

[2]: https://github.com/CMA-ES/pycma

I'm personally interested in this problem and it's a quite active research area right now.

My feeling is that the research is converging to what the paper claims, that the combination of two is the right way to do it and it's a matter of how you combine the two as part of the harness you built that makes the difference.

At the AID-Wild / ACM CAIS 2026 workshop that happened recently, there are plenty of examples in the accepted papers on that.

A great example is AI-PROPELLER: Warehouse-Scale Interprocedural Code Layout Optimization with AlphaEvolve. It uses AlphaEvolve and Vizier to evolve compiler code-layout heuristics. (https://arxiv.org/abs/2606.00131)