“I poisoned my own mind.”
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@glyph “I poisoned my own mind. Maybe I can go back to them in future, starting from scratch and doing them the right way, but for now, they’re shelved.”
The door is still open, not a great ending for the post. I don’t get why people are so tempted by laziness and cognitive decay.
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@glyph I wouldn't have started those projects, as they need a lot of work. The clanker did the heavy lifting, so now we have the tools I wanted to create one day.
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@chroma I can certainly sympathize, but if we want to be convincing (and, like, good people) we need to deal with those feelings of aggression in a more healthy way.
Have you seen https://www.youtube.com/watch?v=y85nqc2zm7M by any chance? It's worth a watch.
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@davidgerard @chroma I don't agree with everything in the video, but what makes it "bad advice"? The harm-reduction approach that she is advocating has been empirically validated for harmful behaviors in general (plenty of literature on substance abuse) but also specifically for AI.
Do you have any countervailing data?
There's also a big difference between AI *advocates* and AI users. Harm reduction doesn't apply to the dealers.
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@dalias @glyph here, you can try proving your claim yourself:
https://github.com/clackups/draftling -
@glyph I love this line: “no matter how many details you put in a prompt to an LLM, there are still decisions you’re ceding to it.”
@BenAveling @glyph I couldn't agree more. When I tell people that ai is dumb as shit and makes the worst possible "decisions", they look at me incredulously. "What decisions is the AI making?" they ask. Have you tried spec driven development they ask. Have you tried plan mode they ask .
Every line of code is a decision. There's an infinite number of ways you can solve a problem. Stringing together plausible code without understanding anything isn't some amazing tech breakthrough.
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@dalias @glyph here, you can try proving your claim yourself:
https://github.com/clackups/draftling@bonkers @dalias I consider asking me to look at LLM output to be an aggressive, antisocial act, which I have detailed in <https://blog.glyph.im/2026/06/adversarial-communication.html>. I am not going to block you immediately because you may not have been aware of this but please do not do so again.
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@davidgerard @chroma I don't agree with everything in the video, but what makes it "bad advice"? The harm-reduction approach that she is advocating has been empirically validated for harmful behaviors in general (plenty of literature on substance abuse) but also specifically for AI.
Do you have any countervailing data?
There's also a big difference between AI *advocates* and AI users. Harm reduction doesn't apply to the dealers.
@glyph @davidgerard @chroma I've wrestled with this problem too and decided that getting mad at every Tom, Dick and Harry who doesn't feel or do the exact same things I do is neither a good use of my energy nor a good way to hold the kinds of meaningful relationships that actually change behaviour.
It's a tough balance to strike because I really don't want to excuse AI as a technology, and there's a lot of justified anger, but it's better to send that anger to people who deserve it and have power over it (read: technology executives, data centre building companies) rather than at people who don't have that power and are just as likely to be victims
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@bonkers @dalias I consider asking me to look at LLM output to be an aggressive, antisocial act, which I have detailed in <https://blog.glyph.im/2026/06/adversarial-communication.html>. I am not going to block you immediately because you may not have been aware of this but please do not do so again.
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As an artist who grew up with tech-minded people telling me how useless and unserious art is, and how I shouldn't waste my time pursuing creative careers, how the social sciences were a joke, who had to listen to them sit in the back of english class and complain when we had to learn about subtext, symbolism, and metaphor and "Why don't they just write what they mean literally?"
It doesn't really give me any satisfaction that an individual of that class of people became self-aware.
@glyph @contrasocial I was, and still am, with the "why don’t they just say what they mean" crowd (for the most part). Yet I always knew programming is art and LLMs are bad.
I can appreciate art, just not everything that falls under that label (think the butter in the corner story). I’m amazed at painters, for example, and great composers.
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@glyph We've all played with LLM coding. Why not? It's intellectual curiosity - something we have and LLMs don't.
The results are sometimes ok, depending on what you expect. Try asking it for assembly language code though, or an unusual language variant, and it falls over.
Then also consider - did you pay for it or us a free tier? And what was the on cost, the energy, water, and addition to the llm bubble size just by using it?Then get back to real coding!
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@bonkers @dalias I consider asking me to look at LLM output to be an aggressive, antisocial act, which I have detailed in <https://blog.glyph.im/2026/06/adversarial-communication.html>. I am not going to block you immediately because you may not have been aware of this but please do not do so again.
@glyph @bonkers I consider it the same, and I can explain why.
Asking me to read the output is asking me to subject myself to the illusion and evaluate what the machine did in a way that's impossible to determine from seeing the output; it would require me to just make assumptions based on my perceptions. A process which, by design, shapes your mind to buy into it.
The only reasonable way to make a conclusion here is from looking at the mechanisms or the high level information-theoretic invariants underlying them.
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@glyph I agree it's a dilemma, and I hope that the bubble bursts soon. Also, if I had to pay the full price of LLM, I'd refrain from using it at all.
In my defense, these are nonprofit projects for the public good. They can easily be continued without the slop engine.
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@glyph @bonkers I consider it the same, and I can explain why.
Asking me to read the output is asking me to subject myself to the illusion and evaluate what the machine did in a way that's impossible to determine from seeing the output; it would require me to just make assumptions based on my perceptions. A process which, by design, shapes your mind to buy into it.
The only reasonable way to make a conclusion here is from looking at the mechanisms or the high level information-theoretic invariants underlying them.
@dalias so, you made a bold claim, but you refuse to prove it on a rather limited code base. It just means that our discussion doesn't make any sense in the first place.
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@dalias so, you made a bold claim, but you refuse to prove it on a rather limited code base. It just means that our discussion doesn't make any sense in the first place.
@bonkers No, you made a bold claim. I made the obvious default claim.
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@bonkers No, you made a bold claim. I made the obvious default claim.
@dalias I made a useful product that I'd never make by myself, as it would take months to code. I reviewed the code and steered the clanker from its mistakes. It is a new piece of software. If anyone finds a plagiarized piece of code, I'll be glad to add the credits.
I don't even need to defend myself, the code is free and there are users already.
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@dalias I made a useful product that I'd never make by myself, as it would take months to code. I reviewed the code and steered the clanker from its mistakes. It is a new piece of software. If anyone finds a plagiarized piece of code, I'll be glad to add the credits.
I don't even need to defend myself, the code is free and there are users already.
@dalias there's one significant difference from human written code: the amount of comments. Humans don't document as much as the machine. It helps the machine in adding more code and it helps a human understand the logic.
So, my bald claim is that it's a useful tool that's not going away any time soon, so it's alright to utilize it if you know what you're doing.
