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this post was submitted on 17 Jul 2026
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Fuck AI
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A place for all those who loathe AI to discuss things, post articles, and ridicule the AI hype. Proud supporter of working people. And proud booer of SXSW 2024.
AI, in this case, refers to LLMs, GPT technology, and anything listed as "AI" meant to increase market valuations.
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This is absolutely not true. The email is very direct, and the specific context doesn't change anything. Here's the full text:
Yes.
And no, that's not the position of the Linux kernel.
I realize that some people really dislike AI, but this is an area where I'm willing to absolutely put my foot down as the top-level maintainer.
Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it.
Or just walk away.
AI is a tool, just like other tools we use. And it's clearly a useful one.
It may not have been that "clearly" even just a year ago, but it's no longer in question today.
There are other questions around AI (like what the economy of it will actually look like in the end), but "is it useful" is no longer one of those questions. Anybody who doubts that clearly hasn't actually used it.
Yes, it can also be a somewhat painful tool, both for maintainer workloads and just from a "it keeps finding embarrassing bugs" standpoint.
But the solution is not to put your head in the sand and sing "La La La, I can't hear you" at the top of your voice like some people seem to do.
The solution is to make sure those LLM tools help maintainers instead of just causing them pain. There's no question on that side.
We're not forcing anybody to use it, but I will very loudly ignore people who try to argue against other people from using it.
And no, AI isn't perfect. But Christ, anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time.
Because it's not like natural intelligence is always all that great either.
The kernel project has been and will continue to be about the technology.
Sure, the social angle of working on open source is important and often a very motivating part of the project, but in the end that's a side benefit, not the point of the project.
This is NOT some kind of "social warrior" project, never has been, and never will be.
In the kernel community we do open source because it results in better technology, not because of religious reasons.
And so we make decisions primarily based on technical merit. Not fear of new tools.
He is such a back stabbing condescending out of touch deplorable libturd. He is the only tool I see. In the movie "their will be blood" when Eli slaps his dad for pulling down his pants... and then he slaps the shit out of him... Thats what I want to do to this fool. Computers are for humans NOT humans for computers. Linux is awsome because of humans... No more with the gipity.. I'd rather be 2nd place then juiced with a limp dick. HOLD THE LINE AGAINST THE SWINE
My brother im christ
Are you ok?
You do realize who you are talking about. Love him or hate him but Linus Torvalds is THE Linux guy
I hate that these discussion often seem to happen in a vaccuum regarding the person.
This man has spent over 30 years writing/maintaining the Kernel. He most certainly knows more than yoi about the kernel the maintainablility and maybe most importantly: The community
Take it down a notch will ya?
People are disappointed that Linus is pro ai, and are concerned that their operating systems are going to become a part of the problem, rather than the solution, or at least the suggestion of hope that Linux is meant to be. Decent options (in many respects) are becoming increasingly rare, when they should have increased. Look at the big players pushing ai, they are not good people.
Being "pro AI" in my book goes a lot further than what they are doing. Using generative "AI" for coding with human oversight and the high standard of code review they have is a far cry from wanting to cram LLM slop into everything as much as possible. I think it's good that they are trying to find security issues like this, for example.
Many people expected and were interested in the development of ai, it was inevitable, and frequently included in science fiction. But as per usual... humans are why we cannot have nice things. The environmental cost of ai is far too detrimental at this stage of its development, especially due to the amount of dickbrains using it for pointless crap. Really bad people are behind it. That is really simple. People are still capable of thinking are they not?
Yeah I think you’re right, when it comes to AI as a coding tool. I heard someone ask something like "where on the scale from flashlight to violin would you put LLM tools for coding". By that, they meant, if you use a flashlight, and it doesn’t work, you’re pretty sure it’s not your lack of experience with the tool - the tool is just broken. But if you play a violin and it sounds like shit, it’s probably because you’re not versed enough to play it (or at the very least you don’t know if it’s you or the violin who’s at fault), assuming you don’t play the violin.
If one finds LLMs unhelpful for coding, is it them not knowing how to play it, or is the tool inherently broken? It’s very arrogant to believe one is so knowledgeable about a tool, one which is in constant development too, that it is not them who is using it wrong, but rather the tool that is wrong.
There’s a plethora of other areas of just criticism of the technology, but I think how useful it is for coding is not one of them.
Aside: your "manmade" line breaks make your comment harder to read on a phone. I guess it’s a hard habit to break, but I would suggest you try. Most places people type text to be read by other these days, one should account for vastly different resolutions and aspect ratios (e.g. vertical & horisontal monitors). Adding in line breaks where it looks good on your screen is like writing text for yourself to read. That’s my personal opinion at least
Reading comprehension is at such a massive cratering low, you really gave criticism on writing style for prose copy pasted from an entirely separate medium written by a completely different author
Jesus Christ people
Take it easy. And don’t just take my one comment as anecdotal evidence of reading comprehension. I will say, first off, I wrote the above shortly after waking up - perhaps not my most analytical piece ever. Furthermore, English is not my first language (kinda not even second). And finally, I have dyslexia, so I literally have worse than average reading comprehension skills.
Also, from my device, it seems only the first 2 paragraphs are in quotation, and everything after "yes" has regular formatting, which gave me the impression of that being the commenters own words, and with the weird line breaks. (I’ll add I know people who have typed like that but have switched, hence I made the remark.)
All I want to say is you shouldn’t use my misunderstanding of the comment I replied to as any evidence of general reading comprehension. It shouldn’t be. And you seem overly affected by this.
The fact that you have to "prompt-engineer" means that the tool has a terrible interface.
In your flaslight analogy, there's an on/off button that doesn't work. You have to flip the flashlight, tap it twice, check the batteries and flip it twice again. Then it turns on.
The fact that LLM coding tools are basically micro-managing with a special twist "knowing how to prompt", makes it a shit tool for a lot of people. And they are justified in thinking so.
You can't hone a skill you have little control over. It's like a hammer that strikes a random area within a certain radius of a nail.
I both agree and disagree.
As for having little control, I feel like that happens in other disciplines too. The best archers need to account for the stochastic nature of wind patterns, and thus they do not always hit their intended target. But still, their accuracy is far greater than a novice. There is both skill and "luck" - if you will - involved in the process. You definitely can hone a skill you have little control over in the beginning, I believe. Maybe this is the analogy that should’ve been made.
I will say, "knowing how to prompt" feels like a weird skill, and I think the way we interface with these tools is kinda wacky. Regular text feels to fuzzy.
But it does help immensely, I find, to take every wrong agentic coding output as a learning experience. When I know the answer, and the agent failed, I ask myself why it didn’t fint it. Taking these opportunities has led me to be more proficient in the use of skill files, agent files, subagents, context window management, etc., all which have improved the agents output massively. I feel like a year ago, it was just prompting and copy-pasting (at least for me), but now, with tools like OpenCode, I can get a better looping effect with fewer errors.
I am curious about your findings
Don't forget we are talking about a tool.
A good tool is easily documentable, and then usable with said documentation. A good tool has perfect repeatability It is easy to predict the outcome of using a good tool.
Current LLMs have neither. For all the user knows, it's a black box that takes input and poops out output. You can only steer the output after some output has already been given.
I think we disagree on the nature of a tool. Or maybe I am thinking about more than a "tool", but not using the appropriate word for it.
Image riding a very fast horse. There is no perfect repeatability, it might veer off, or react to something you didn’t see, but a good rider would probably manage to arrive at the intended destination. I think I view it the same with agentic coding.
Now, I agree a horse is not a tool, and that’s why I mentioned that my language is perhaps a bit imprecise. (I guess you could even call it an agent.) But maybe an "instrument" or an "implement" fits, although that’s a bit cold wording for a horse in general, as they have other qualities, as being cute etc.. But I think you get my point.
I very much think LLMs can fall under the description of "useful implement for coding" today. But I do think it is a very poor knowledge retrieval implement. In fact I sucks for all these one-off questions, I my opinion.
I think the more interesting discussion is about how these AI companies consolidate power even more, how they steal data, how they pollute like crazy. But I think people who dismiss their use in coding perhaps view LLMs more like a flashlight and less like a very fast horse moving you from A to B.
Context engineering is a skill analogous to communicating a problem to fellow maintainers. This typically involves articulating the issue within an issue tracker, pull request, or comment using written text. Therefore, proficiency in "prompt engineering" is essentially a measure of one's articulacy.
So it's not a "useful tool for coding" then, if the quality of the output depends of one's ability to articulate in a way that tickles the LLM "the right way".
Also, no matter how well you articulate, the output is still somewhat random. You can produce two different sections of code with (essentially) the same prompt, which also just means that theres an amount of luck and percieved randomness in a tool.
Imagine you want a piece of software written but you're hiring it out, like a lot of corporations do. You write up a loose specification and hand it to two different dev shops and you'll get two wildly different results. The tighter the spec, the closer the results will be.
It's not much different from that.
Indeed. I agree that it's not a tool, but a type of outsourcing.
Following my analogy with the archer, promting the right way is like accounting for wind. And again, no matter how much the best archers in the world account for wind, they do sometimes miss. Still very impressive how high their skill is, even with randomness involved. And with agentic coding, one can always shoot twice.
TLDR: In short, like a lot of AI use the biggest problem is more how other people are using it that I have little control over.
The thing is that CodeGen utility varies greatly on what is being advocated and what situation it is being applied to. CodeGen getting things going when the operator isn't strongly opinionated about the details for fairly common patterns is fairly strongly in the wheelhouse. It is somewhat worse at amending a project in the same broad ways it was able to do when starting from scratch, even a project the model itself generated. So as you progress, it is more and more likely that a human will need to understand what is going on to be effective in modification. This presents a problem as people work themselves into a mess and can't get out of it and this causes a fair number of projects to just get abandoned because they can't go anywhere.
Even as it has demonstrable utility, the real world implications can be a mess. For example, the other week someone used agentic AI to open up 70 'security findings' on a project I work on. To it's credit, it found one actual issue, and while another issue was incorrect, looking into it I did find a separate issue it didn't notice, so I got two fixes out of it. However I had to deal with 68 completely stupid things that weren't anything. The operator at least up front sent an email that they didn't understand any of it and how much was real, but wanted to share in case any of it is useful. But I guess that's the price I pay for the two valid issues that might have otherwise not been caught. Then a few days after settling those, another user opened up over 60 and they were all dupes. Then the next week another user opened up a bunch that were all dupes too. Now it's ridiculous. One could argue that I could fight fire with fire and put an LLM on triaging the issues and closing out the dupes, but that means random github users can now make me spend my money on LLM services just by opening issues. Further, after being on the receiving end of AI chatbot triage in customer support, I hate inflicting that on the humans opening issues.
Then of course there's the code submissions and expectations around how I should handle them. There was a longstanding understanding that folks try their best, but implementing feature requests takes effort and folks are broadly understanding at delays or being a bit down the priority list. Now someone will Claude up a merge request instead of an issue and be impatient because "Claude already did the hard work, all you have to do is accept it", and it's a mess of code to review. It's not like the code at the hands of the operator is exactly good, for example someone sent a merge request because some feature raised an exception for them and blocked it from working and Claude "fixed" it. Problem is Claude changed the code to catch the exception, do nothing, and just say that it worked. In their test scenario, the feature was trying to make things the way they already were, so a no-op was no problem, but when I made their test case actually start from another state, it failed but still said it worked.
Another project I used to be a part of recently got handed over from the maintainers that long maintained it and lost issue to a super Slop-happy AI user. They got it rigged so it's all agentic and "addresses all issues and resolves all pull requests automatically from anyone". The project had some poor issue hygeine, so this meant the agentic code was doing things like fixing an issue from 2017 where the user complained it didn't work with Ubuntu 16.04. No idea if the fix actually worked, but it did make code changes that realistically no one would care about if they only did what they want. Except now they are getting bunch of new issues because they say "hey, the latest update broke a bunch of stuff I relied on", and another said "hey, it was great to see my issue get fixed last week, but this week the issue is back?" and messages saying "the update pace is ridiculous, why are there 3-4 releases a day, the former cadence was once a quarter". It's become a broiling mess of chaos because some AI enthusiast decided to make a nearly abandoned project that people were using a playground for AI usage. Dude even said point blank it's fine, just open an issue and AI will fix it for you and if it breaks, then someone else just open another issue and it'll get fixed and he is confident that eventually the users will shape the project into some equilibrium that way, so he has to do very little except pay for the tokens.