This is a good thesis but it does lean a bit too hard on a vague 80/20 metaphor. It kind of romanticises old-school engineering struggles while downplaying how much of past learning was just wrestling with crappy tooling or poor docs. Things are much better now, I wouldn't want to go back. The stronger argument would not just be the old way is better, but that we need a way to preserve judgment that used to be developed through the struggle.

> we need a way to preserve judgment that used to be developed through the struggle.

it's true. once you've gone "deep" for a few years in at least one technical domain, that depth transfers pretty well to the next big new thing you didn't know you'd have to learn when you started. i think the fear about the new regime is that people will be denied the opportunity to obtain depth in anything. like we'll encounter the human equivalent of domestication syndrome.

i remember when certain loud individuals believed that {managed memory | IDE auto-complete | statistical db optimizers | programming languages higher than assembly level | ...} were going to make everyone stupid. but the higher-order systems have continued to present rich problems to engage the mind and spark creativity. this era feels different though, the worry more pressing.

Right, I find that AI tools combined with solid domain knowledge are incredibly effective. Yeah, if you try to one-shot a complex distributed system you'll end up with a mess, but the same thing would happen if you tried to do it yourself in the space of a day - you're still reasoning and applying experience, it's just you have an automated tool to take care of generating the source code.