AI assist in software engineering is unambiguously demonstrated to some done degree at this point: the "no LLM output in my project" stance is cope.

But "reliable, durable, scalable outcomes in adversarial real-world scenarios" is not convincingly demonstrated in public, the asterisks are load bearing as GPT 5.2 Pro would say.

That game is still on, and AI assist beyond FIM is still premature for safety critical or generally outcome critical applications: i.e. you can do it if it doesn't have to work.

I've got a horse in this race which is formal methods as the methodology and AI assist as the thing that makes it economically viable. My stuff is north of demonstrated in the small and south of proven in the large, it's still a bet.

But I like the stock. The no free lunch thing here is that AI can turn specifications into code if the specification is already so precise that it is code.

The irreducible heavy lift is that someone has to prompt it, and if the input is vibes the output will be vibes. If the input is zero sorry rigor... you've just moved the cost around.

The modern software industry is an expensive exercise in "how do we capture all the value and redirect it from expert computer scientists to some arbitrary financier".

You can't. Not at less than the cost of the experts if the outcomes are non-negotiable.