Open Question 2.2: Framework for studying feature learning at large width. Is there a simple, computationally tractable calculational framework — potentially making realistic simplifying assumptions — that allows us to quantitatively study feature evolution of a general class of neural network in the rich regime and which requires tracking less information than the DMFT framework of [Bordelon and Pehlevan (2022)]?