[arw0n]

I've recently had an interesting discussion on AI usage by students with a couple of friends who are all professors or lecturers in different fields. They report that AI makes their job harder, especially because it widens the gap between students:

Students who would have straight up failed before now produce passable essays/projects, but do not understand what they are handing in. They outsource their thinking and are overall worse than before. Students who would have excelled already pre-ai, are now even better. They use AI to learn more effectively, do broader research, and have more time to do deep research because they can outsource the grindy stuff.

This is very similar for software engineers. I'm not much faster at implementing features than before AI, despite heavily relying on agentic coding (95% of code is ai generated), but I've had significantly fewer bugs in production, less feature change requests (because w spend much more time designing/experimenting), and we are able to drive-by refactors or vulnerability fixes we would have grudgingly ignored before.

My coding skills are atrophying, but that was never interesting to me anyway. I'm getting better at systems design, cyber sec, data modelling and requirements engineering, because I have much more time to spend on it now. If LLMs disappeared tomorrow, I'd have to relearn coding, but I think it is significantly more likely that hand coding will become a specialist niche for experts.