piet-gpu contributor here. You're right that supersampling is the easiest way to achieve AA. However, its scalability issues are immense: for 2D rendering it's typically recommended to use 32x for a decent quality AA, but as the cost of supersampling scales linearly (actually superlinearly due to memory/register pressure), it becomes more than a magnitude slower than the baseline. So if you want to do anything that is real-time (e.g. smooth page zoom without resorting to prerendered textures which becomes blurry), supersampling is mostly an unacceptable choice.

What is more practical is some form of adaptive supersampling: a lot of pixels are filled by only one path and don't require supersampling. There's also some more heuristics that can be used: one that I want to try out in piet-gpu is to exploit the fact that in 2D graphics, most pixels are only covered by at most two paths. So as a base line we can track only two values per pixel plus a coverage mask, then in rare occasions of three or more shapes overlapping, fall back to full supersampling. This should keep the cost amplification more under control.