The scarce input for applying reasoning models is skilled human effort.

You need the expert human to both direct and effectively evaluate the model's output.

It can give absurd leverage to experts, but without an expert driving it, you get performative rigor.

That is, superficially high quality, but often a gilded turd^[we].

This effect gets stronger the more believably LLMs can give superficially high-quality answers^[wf] on more topics.