Fair enough!

I've been vocally against Linus AI advocacy, but I do understand all the points you make here.

I don't like that a lot of stupid people will take Torvalds use and embrace of AI as gospel that AI is some be all end all.

I also LOATH that he is indirectly benefitting fascist corporations that committed the largest theft in human history.

But the code is good 🤷‍♂️

To say I am conflicted, is an understatement.

Plus all the employees who've been forced to produce and sift through that garbage code, because their bosses bought into the hype and don't see the software for what it actually is.

Isn't the AI problem the vast amount of resources needed to produce code?

I'd like to steal this comment for my Detailed And Nuanced Opinions On AI.

Yet even for those Joe Normals, I kinda like the democratising effect that they're now able to produce software, or modify existing software for their own use. Just don't fool yourself into thinking it's enterprise grade. Understand your limitations. And don't spam open source projects with slop PRs because you think the AI makes you a software wizard.

This is an old argument

reading code you didn't write is genuinely more tiring than writing it

What I keep saying. Good take except that you don't use "AI" tooling, you use copyright evasion slop tooling.

Linus knows this codebase better than anyone alive

Does he? Is it even possible to know the entirety of the Linux kernel within one head?

Verifying LLM code isn't necessarily harder than verifying a human PR. I hope that this also boosts automated test tooling so that it also gets easier to test these PRs, since the focus will shift to review rather than writing.

Plus studies on skill decay when using AI. Also the linux maintainer onboarding pipeline—which was already critically endangered—is now no longer building understanding through writing code, just monitoring it's generation.

I personally think you need to write a language by hand without AI doing it for you to learn in detail. It's like trying to learn how to do math or how to write mandarin by just supervising an AI doing it... you need to do it yourself. Supervising is fine if you're already fluent in mandarin and have been writing it for years and years. If you're just learning it's less than useless. If anything its directly harmful to learning.

Same with speaking a language yourself without crutching your native language as the best method to learn to speak it (immersion)

Edit: The long term externalities of AI—like pretty much everything nowadays—is going to be made worse by short term thinking. Quarterly profits and yearly results take precedence over long term skill development. Even OSS like linux will eat its seed corn out of expediency because of a lack of maintainers and new candidates being onboarded into the ivory tower mailing lists...

Human review of AI is sufficient in theory, but in practice it's never as thorough as the understanding you get writing it yourself. It's hard to avoid AI, but it is a constant invitation to laziness.

One thing I'm noticing about AI code is it's very, very task oriented. Like it will produce code, that works for the one objective, but absolutely will not account for other interactions with other parts of the system. It's really bad at juggling multiple priorities so for every solution it creates, it causes another 2 problems with other parts of the stack. Human coders would design a solution that takes those interactions into account from the ground up. With an AI solution, you kind of have to rebuild those interactions as an afterthought, which is where a lot of failures occur. Since interaction of multiple subsystems is kind of the whole point of a kernel... I have concerns.

it shouldn't be that impactful negatively that AI is being used

Doesn't it invalidate the GPL? Open source licenses depend on copyright, and LLM-generated code isn't copyrightable.

(Also, it can't be proven not to contain plagiarised proprietary code, in fact it's quite likely that it does; between this, the testing / review burden, and the mental decay of developers that use LLMs instead of coding, this pretty much kills open source projects, in several different ways to make sure they stay dead...)