Same. We've all fooled ourselves into believing that an LLM / stochastic process was finally solved based on a good result. But the sample size is always to low to be meaningful.

even if it works as described, I'm assuming it's extremely model dependent (eg book prerequisites), so you'd have to re-run this for every model you use, this is basically poor man's finetuning;

maybe explicit support from providers would make it feasible?