What the contemporary dev environment teaches about scale is that it barely matters until you hit certain thresholds, and then it suddenly dominates everything.

What the contemporary dev environment teaches about scale is that it barely matters until you hit certain thresholds, and then it suddenly dominates everything. A corollary of this is that as your program becomes more complex, relatively more of the code ceases to matter to performance, because its purpose is to configure a certain inner loop, and the inner loop becomes the only real bottleneck. So, when coding for very small systems(retro or embedded) the whole program architecture matters, but at hyper scale, the problem is seen mostly in terms of efficiently distributing the load, and only deeply optimizing the program in very specific places. A good starting point for thinking about this is a system like BitTorrent: The ideal torrent experience will most likely use multiple peers, and the performance needs to remain consistent as the number of peers increases and the load becomes more complex to distribute. But it's not really about the local performance so much as it is maintaining the overall network conditions - if every peer is doing "OK" at serving and retrieving files that's better than a very good experience served inconsistently.