“I poisoned my own mind.”
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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.
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@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
@brib @glyph @davidgerard Uh, oh, excusing people because they're weak-minded or surrender to “convenience” is not the way to go, I believe.
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@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.
@bonkers The kind of comments in LLM codeslop are the opposite of useful. They do not document motivations why something was done the way it was, connections to external contracts, etc. They're imprecise restatement of what's in the code. The same bad types of comments novice human codemonkeys write when told to comment their code better.
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@bonkers The kind of comments in LLM codeslop are the opposite of useful. They do not document motivations why something was done the way it was, connections to external contracts, etc. They're imprecise restatement of what's in the code. The same bad types of comments novice human codemonkeys write when told to comment their code better.
@dalias I assume you didn't open my link
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@dalias I assume you didn't open my link
@bonkers Of course I didn't.
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@bonkers Of course I didn't.
@dalias so, another bold claim without any ground.
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@dalias so, another bold claim without any ground.
@dalias sorry mate, but you have no fucking clue what you're talking about.
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@dalias so, another bold claim without any ground.
@bonkers No, it's not a "bold claim". There is no model of reality or how anything works in these systems, only pattern regurgitation in ways that correlate/align with context. If you get any comments that appear to explain motivations, they're copies of someone else's ideas from a similar context, not something reasoned to apply to your code.
The way you support or refute what I'm saying is through examination & analysis of the mechanisms, not examination of the output and whether it looks like what you would expect from human reasoning. "Looks like human reasoning" is the deception working as intended, and if you're trying to assess it from that standpoint, you're falling for the brain rotting program.
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@bonkers No, it's not a "bold claim". There is no model of reality or how anything works in these systems, only pattern regurgitation in ways that correlate/align with context. If you get any comments that appear to explain motivations, they're copies of someone else's ideas from a similar context, not something reasoned to apply to your code.
The way you support or refute what I'm saying is through examination & analysis of the mechanisms, not examination of the output and whether it looks like what you would expect from human reasoning. "Looks like human reasoning" is the deception working as intended, and if you're trying to assess it from that standpoint, you're falling for the brain rotting program.
@dalias no, I'm just saying that it's a useful tool in an experienced engineer's hands. Everything else is your own assumption.
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@bonkers The kind of comments in LLM codeslop are the opposite of useful. They do not document motivations why something was done the way it was, connections to external contracts, etc. They're imprecise restatement of what's in the code. The same bad types of comments novice human codemonkeys write when told to comment their code better.
@dalias @bonkers at my job, I work on the open source software of a very famous science project, so people often think they'll "help out" by pointing agents at our codebase. The LLM slop that well-meaning people have started foisting on me and my colleagues almost always has the same thing in common; it's almost always extraordinary and unnecessarily verbose. Pull request descriptions are long paragraphs of repeated information with bold section headers and emoji. Bits of logic that could be a single line are instead broken into multiple hyper-specific functions. function docstrings are useless reframings of exactly what the code says, without actually saying what situations the function should be used for. It's a mental burden that these people dump on us and say "you sort this out, I'm so helpful!" and I just want to reach through the screen and shake their shoulders and tell them that if they actually want to be helpful they can just read our contributing docs and write stuff themselves!
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@dalias @bonkers at my job, I work on the open source software of a very famous science project, so people often think they'll "help out" by pointing agents at our codebase. The LLM slop that well-meaning people have started foisting on me and my colleagues almost always has the same thing in common; it's almost always extraordinary and unnecessarily verbose. Pull request descriptions are long paragraphs of repeated information with bold section headers and emoji. Bits of logic that could be a single line are instead broken into multiple hyper-specific functions. function docstrings are useless reframings of exactly what the code says, without actually saying what situations the function should be used for. It's a mental burden that these people dump on us and say "you sort this out, I'm so helpful!" and I just want to reach through the screen and shake their shoulders and tell them that if they actually want to be helpful they can just read our contributing docs and write stuff themselves!
@zrb @dalias true, and the only useful thing here would be rejecting such PRs without spending much time on them.
They could, theoretically, utilize the clanker to produce the change, but they should at least be able to understand and summarize it.
My point is, it's a tool. A hammer could also be used for building good stuff and for killing people.
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@zrb @dalias true, and the only useful thing here would be rejecting such PRs without spending much time on them.
They could, theoretically, utilize the clanker to produce the change, but they should at least be able to understand and summarize it.
My point is, it's a tool. A hammer could also be used for building good stuff and for killing people.
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@bonkers @dalias that was the first thing we did, and really all that does is weed out the people and automated agents that respect policies, and select for people and agents that don't. Companies already don't care about open source licenses, and don't respect
robots.txtwhen scraping, so it's no surprise they don't respect community policies either. -
@bonkers @dalias that was the first thing we did, and really all that does is weed out the people and automated agents that respect policies, and select for people and agents that don't. Companies already don't care about open source licenses, and don't respect
robots.txtwhen scraping, so it's no surprise they don't respect community policies either. -
