Sheafification – The optimal path to mathematical mastery: The fast track (2022)

This is wrong. In Computer Science language, human learning works in greedy way. We make locally optimal decisions in life. We cannot learn something in globally optimal way. We learn something in locally optimal way. And by repeating that we can reach somewhere at some point.

Here's my take on this - you should try to organize your local space of affordances and rewards in such a way that locally optimal choices will over time get you closer towards your global objective.