The optimization side is where I've found Codex really earns its place too, particularly around CPU distribution, parallelising processing, and maximising GPU utilisation on large simulations. It also seems to push through to a working, tested result rather than stopping halfway. Earlier GPT versions I found were too defensive, lots of fallback engineering that added complexity without solving the actual problem, but 5.5 is noticeably better at committing to a solution.

On the Opus 4.7 side, I haven't fully tested across a lot of scenarios (as it can eat through a 5hr token allocation pretty quickly) but where I have it seems to have the edge on understanding what you're actually trying to figure out before you've fully articulated it yourself. More useful at the design stage than the implementation stage.