Most quality standards live in your head. You know the answer should be short, or written for a non-specialist, or structured so a downstream step can parse it, and you assume that because you know these things the model will honor them. It will not, because it cannot see them. A standard you hold silently has exactly zero effect on the output. It…

The largest single lever over the quality of a model’s output is not the model, the sampling settings, or the length of the prompt. It is how completely the instruction defines what a good answer would be. An instruction that leaves a decision open does not leave it unmade. The model makes it, silently, on your behalf, and you find out which way…