It’s interesting to see AI being used for something as practical as debugging a Linux issue. I think the bigger question is how much developers can rely on AI without losing their understanding of the underlying code. AI can clearly speed things up, but human review still seems essential.
I think its pretty clear that an OG hacker like linus using AI as a helpful assistant is very different from a junior dev using it as a crutch
The question now is how to develop proper software engineers who have the old school skills first and foremmost, and then are able to use the assistance of an AI
Exactly. AI should complement strong fundamentals, not replace them. Developers still need to learn how to think, debug, understand systems, and make technical decisions independently. Once those foundations are solid, AI becomes a powerful multiplier rather than a crutch.
It’s especially essential to mark the code as AI generated. AI makes mistakes just as humans do. Problem is AI makes different kinds of mistakes than humans.
A human will tend to forget to do something they were supposed to do. An AI will do a bunch of unnecessary shit.
Also you can tell that a human didn’t put a lot of thought into some code (no comments, sloppy variable names) so you’re more likely to say “yeah ok, I used to make that kind of mistake when I was younger” and just fix it. AI generated code will have all kinds of comments which normally makes you more hesitant before making a change. It looks like someone really thought through what they were doing, but in reality it’s something generated by an LLM and no real thought was given to the code.
It’s interesting to see AI being used for something as practical as debugging a Linux issue. I think the bigger question is how much developers can rely on AI without losing their understanding of the underlying code. AI can clearly speed things up, but human review still seems essential.
I think its pretty clear that an OG hacker like linus using AI as a helpful assistant is very different from a junior dev using it as a crutch
The question now is how to develop proper software engineers who have the old school skills first and foremmost, and then are able to use the assistance of an AI
Exactly. AI should complement strong fundamentals, not replace them. Developers still need to learn how to think, debug, understand systems, and make technical decisions independently. Once those foundations are solid, AI becomes a powerful multiplier rather than a crutch.
It’s especially essential to mark the code as AI generated. AI makes mistakes just as humans do. Problem is AI makes different kinds of mistakes than humans.
A human will tend to forget to do something they were supposed to do. An AI will do a bunch of unnecessary shit.
Also you can tell that a human didn’t put a lot of thought into some code (no comments, sloppy variable names) so you’re more likely to say “yeah ok, I used to make that kind of mistake when I was younger” and just fix it. AI generated code will have all kinds of comments which normally makes you more hesitant before making a change. It looks like someone really thought through what they were doing, but in reality it’s something generated by an LLM and no real thought was given to the code.
Why is your code so messy that it needs comments everywhere? Comments should pretty much be reserved for special cases anyway