It's already increased a bit in the microprocessor world with the rise of GPUs, but that "just" puts supercomputer-style vector processing in SBCs and laptops. It isn't as new of a concept as systolic arrays, for example; those can be fast even on slow hardware if you pick your problem right, just like how GPUs are only speed demons on certain tasks. Well, if we can't beat problems to death with increasing scalar speed, it might give us more incentives to design ever-more-specialized chips which solve specific problems extremely effectively even if they're comically useless for general-purpose computing.
For those not immediately familiar with the terminology: "scalar" is Single Instructions, Single Data.
A big problem is heat. But stacked designs produce less heat overall, just in a smaller area. That can actually make heat dissipation more centralized and more efficient (due to higher thermal gradient) so I think it's a solvable problem.
I do agree, the longer term will lead to stacking, I'm just not sure how far off that is in realistic terms, and if the complexities may outweigh the benefits in a lot of use cases.
The node shrinks are definitely slowing and have for a several years.