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I think you're probably right that the article was AI-assisted, but (if so) it's important not to confuse that with the thing the article is about. Google wouldn't pay $90k for a hallucination.

I don't mean that as a criticism—the question of how to receive AI-processed content is chaotic right now. I'm working on a post about that here: https://news.ycombinator.com/item?id=48887149.

Btw, Nebula Sec is a YC startup in the current batch. We've been working with them on how to launch on HN, and one of the things I've been trying to explain is that the HN audience won't respond well to LLM-generated reports. The underlying work, though, is impressive. These guys know what they're doing—the OP is by no means their only significant find—and the fact that they're doing it with an agent, rather than the traditional way, is significant.

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A thing that notably triggers my allergies is that if significant human effort went into something, a few paragraphs written by a human seems like a trivial additional investment; if that last touch is missing, it's really hard for me to extend the benefit of the doubt that there really is something there.

Obviously this is only one signal among many, one that can be overruled, but the ick remains regardless.

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I agree to an extent, but there are many exceptions, so one can't really withhold the benefit of the doubt.

For example, non-native English speakers (as is the case with these guys IIRC) frequently use these tools. Maybe they shouldn't—as I've been telling a lot of people who email, mistakes are rapidly becoming a sign of authenticity at this point—but the belief that they need to is widespread, and this doesn't mean they didn't do significant work.

(Side note: it's a common assumption that machine-translated text is in a different category from LLM-edited text. From what we're seeing, that assumption is unfortunately completely wrong.)

Another important case is people with disabilities who find these technologies assistive. Again, one can argue that they're increasingly better off just posting their own writing in the raw, but this is a pretty obscure point to get across to people.

Beyond those cases, a lot of people just don't write easily, and/or don't feel their writing is any good. A lot of them are using LLMs to compensate for that, and this by no means implies that their work is bad. Maybe they just have a phobia about writing and/or don't express themselves well that way.

People who enjoy writing or are confident writers fail to understand how emotionally fraught writing is for many others.

Personally I'm down with the "writing is thinking" view, from which it follows that bad writing is bad thinking. But it doesn't follow that "thinking is writing" - that's a much stronger claim, from which it would follow that good thinking is good writing—and this I think is false.

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Non-native speakers have learned and improved their English for decades by trial-and-error, let’s stop using that as an excuse to use LLMs. I have been there, and making mistakes is how one learns to communicate effectively in another language.

If one doesn’t put effort in their writing, I am not going to put effort to read whatever slop they put out instead. Simple as that.

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What you say implies that people should "learn and improve their English" before posting their work to HN. I'm not with you on that, and here's why: we're trying to optimize for the most-intellectually-interesting site, not the most-English site: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor..., even though people do have to post in English here.

That may sound like too fine a distinction, but it isn't. Here's an example: Show HN: Getting GLM 5.2 running on my slow computer - https://news.ycombinator.com/item?id=48842459, which was the #1 thread on HN a couple days ago (https://news.ycombinator.com/front?day=2026-07-09).

That user is a non-native English speaker who helped get his posts into a format that HN could appreciate. His work is obviously excellent—the community response was unambiguous. But I don't think it would have made it through without our help.

I'm sure you weren't saying that if someone can't describe their work in good English then it must be slop, but the space is larger than you make it sound. Which is unfortunate in a way—it would be easier to narrow it down, but then we'd miss posts like that one.

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Pie-in-the-sky synthesis: translation is easy these days, so maybe non-english writers can and should just write in their own native language and let the readers provide their own translation. Perhaps English no longer needs to be the lingua anglais of western tech writing :p
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I don’t buy it, Dan, because non-native English speakers were somehow managing to produce, publicize, and communicate before LLMs did the heavy lifting for them. Perhaps they had human assistance before, but the slop that’s so endemic today reminds us of its value.
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Not on HN they weren't. Right?
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Non native speakers have been on HN since its inception. Unless you mean something else?
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Sorry, I was posting hastily and can see how that was unclear. Unfortunately I've forgotten my point.

Perhaps it was this: there are many non-native English speakers who have valuable things to contribute to HN, who don't yet have sufficient English or don't feel they do, and therefore resort to LLMs to do their English for them. Should they automatically be excluded?

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They should be included! But there's a difference between machine translation and technical-writing-using-an-LLM, in my opinion. One has a lot more humanness to it, still.
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You said earlier that we don't allow LLM-generated content on HN itself (i.e., the comments). So, at least in principle, that's already taken care of through exclusion.

If you mean the linked content: can come from anyone and anywhere--it's just whatever someone submits and is deemed good enough by The Algorithm to get attention. So that's not "HN content" - the content exists independently of HN. As for that, I'll repeat myself: the scientific community has managed somehow to intercommunicate for centuries despite language barriers before LLMs existed. (English was neither Einstein's nor Madame Curie's first language.) It's an existence proof that LLMs aren't needed to overcome those barriers.

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It frankly doesn't matter how much human effort went into finding the vulnerability, it just matters if it exists, how severe it is, and how easy it is to exploit.
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If an exploit is actually working, human effort is void and the ML has done a great job. However most of the time its hallucinating, confidently talking gibberish in technical lingo. This phenomena is only amplified by those who try to make a quick buck without effort using older models, not reviewing output or prompting properly ('find me bugs in Linux, make no mistakes')
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There is no if, it works, people have video proof, google confirmed, Linux patched and fixed. And you still believe this is AI gibberish
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You should put a note in Find a Cofounder not to do that as well. Huge turnoff for me, though I guess a great filter.
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No this is normal programming terminology. Here I am using 'shape' in this sense back in 2021:

https://www.marginalia.nu/log/40-wasted-resources/

and even more similar usage again in 2023 'the shape of the algorithm' (which was post-claude I guess, but this was before I even tested any LLM):

https://www.marginalia.nu/log/87_absurd_success/

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We apologize for the confusion. We used AI to run final grammar pass and didn't noticed it changed some wording (shape is one of them). Will be more careful in the future
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I've used phrasing like this from time to time before, like when trying to compare two ideas that are unalike but have some fuzzy similarities. I wouldn't use it to describe functions but "problems", "solutions", and other fuzzy things.
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When working in Elixir, everything is about the shape of things. I have now taken that word usage from that ecosystem because I find it useful.
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Isn't this just observation bias? "If I haven't encountered something, then it must not be real?" (Paraphrasing)
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I must confess that I asked a leading question. At no point did I say that the usage wasn't real; by way of dramatic omission I was more pointing to the fact that a common ECMAScript/React-ism is overrepresented in Claude's training set to the point that it's being applied to situations not involving duck-typed languages.

I'm not a grammatical prescriptivist but I find it viscerally troubling that a bunch of LLM cargo-culted terms are starting to inform how we talk about our work.

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Except that working with Claude has me saying things like shape lately. I think I like it.
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talking about data and function shapes is quite common in functional programming world

https://blog.jle.im/entry/functors-to-monads-a-story-of-shap...

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