I think there is one problem with defining acceptance criteria first: sometimes you don't know ahead of time what those criteria are. You need to poke around first to figure out what's possible and what matters. And sometimes the criteria are subjective, abstract, and cannot be formally specified.

Of course, this problem is more general than just improving the output of LLM coding tools

I work as an ML engineer/researcher. When I implement a change in an experiment it usually takes at least an hour to get the results. I can use this time to implement a different experiment. Doesn't matter if I do it by hand or if I let an agent do it for me, I have enough time. Code isn't the bottleneck.

I also heard an opinion that since writing code is cheap, people implement things that have no economic value without really thinking it through.