Formal verification is a nice idea but it's a big hill to climb from where we're at. Most people can't even get agents to robustly E2E QA code, which is a much smaller hill to climb for (probably) larger benefits. I'm sure this area will improve over time though, since it is an eventual unlock for fully autonomous engineering.
I think the section on AI from Zero to QED (a proofs in Lean/lang guide) gives a sober path forward from the perspective of market-makers and trading:
"Imagine market infrastructure where agents must prove, before executing, that their actions satisfy regulatory constraints, risk limits, fairness properties, and eventually machine-checkable proofs of Pareto efficiency of market mechanisms. This is a big, hairy, ambitious goal. Not “we reviewed the code” but “the system verified the proof.” The agent that cannot demonstrate compliance cannot act."
https://sdiehl.github.io/zero-to-qed/20_artificial_intellige...
I think for most complex systems, robust E2E QA is a waste of money. A small handful of E2E smoke tests and thoughtful application of smaller tests is usually enough. Though to be fair, agent aren't good at that either.