Yeah, when you start getting into this stuff and see your first dataset with over a hundred MRIs, and actually start manually inspecting things like skull-stripping and stuff, it is shocking how dramatically and obviously different people's brains are from each other. The nice clean little textbook drawings and other things you see in a lot of education materials really hide just how crazy the variation is.

And yeah, part of why we need more within-subject and longitudinal designs is to get at precisely the things you mention. There is no way to know if the low ICCs we see now are in fact adaptation to the task or task generalities, if they reflect learning that isn't necessarily task-relevant adaptation (e.g. the subject is in a different mood on a later test, and this just leads to a different strategy), if the brain just changes far more than we might expect, or all sorts of other possibilities. I suspect if we ever want fMRI to yield practical or even just really useful theoretical insights, we definitely need to suss out within-subject effects that have high test-retest reliability, regardless of all these possible confounds. Likely finding such effects will involve more than just changes to analysis, but also far more rigorous experimental designs (both in terms of multi-modal data and tighter protocols, etc).

FWIW, we've also noticed a lot of magic can happen too when you suddenly have proper longitudinal data that lets you control things at the individual level.