johnfn

Non-math fields tend to reuse regular words as jargon

Isn’t this the field with a “closed” “set”, an “open” “set”, oh and also a “clopen” “set” for some reason?

Why would rewriting Claude code, an app which probably has 30-40 (I might be significantly underestimating) extremely active contributors be easier than rewriting Bun, which has fewer contributors and almost certainly also less lines of code?

Pangram clearly says "Remember, our results aren’t based on this evidence." when you turn on supporting evidence.

Sure and OpenAI articles aren’t negative because of Sam Altman, Anthropic articles aren’t negative because of Dario etc…

The article does not engage with its subject matter with good-faith engagement and curiosity. "Always has been. Always will be." is, inherently, the author's lack of engagement with the subject matter. "They cannot see the world outside" is a shut door that does not admit curiosity or an interesting comment. And so you are seeing this reflected back in the response.

Do you really think threads like [1], [2], [3] are pro-AI? I literally just selected three at random from today's feed. I think the only positive threads about AI here are typically new model releases.

[1] https://news.ycombinator.com/item?id=48923079 [2]: https://news.ycombinator.com/item?id=48921461 [3]: https://news.ycombinator.com/item?id=48926590

Speaking personally I was not particularly moved by the article because I have seen the same thing, in different shapes, thousands of times on HN and elsewhere. Really, AI can't feel and therefore it is inferior? Never heard that one before. Really, an AI can't feel friction and therefore can't adapt to it? Daring today, aren't we? (And a more interesting question: is that even true..?) I realize I am being unnecessarily harsh here, but this article is very much preaching to the choir on HN, which has an anti-AI bent. No one is showing up because there's nothing really to show up to here -- and that is why you are left with "sly jibes" and not much else.

I think of LLM tells like grammatical issues. If you read an essay full of grammatical mistakes you’d immediately start thinking less of the author, even if the essay isn’t about grammar. You wonder if someone who doesn’t pay close enough attention to catch a mistake “their” from “they’re” took attention to the rest of their work. This isn’t necessarily fair because the content of the essay might still be good. But on the internet I don’t have the time to evaluate the quality of every piece of writing I come across. It is very much the burden of the author to, as fast as possible, prove to me that the rest of the article will not waste my time. There is already so much content to read, and in some sense the amount of time to evaluate if an article is well-founded can be unbounded (imagine how long it would take to tell if an article about why a programming language is thoughtful without going out and also learning that language).

I find LLM-isms to be exactly the same as grammatical errors, but worse. At least when writing before you had to take the effort to type every word, so there was a minimum amount of effort you’d need to expend. If you aren’t catching obvious things like “the honest part” then that likely says bad things about your attention to detail elsewhere.

I mean I think I agree with most of what you’re saying, I do agree it’s a bit of a forest grasslands scenario, but the key difference is that he said there’d be a forest at a time when you’d be hard pressed to find someone saying there would be even a microorganism on the ground. It’s pretty darn easy today in 2026 to say wow, his predictions were so off. And it is true: they are very wrong compared to any other prediction made in the last 5 years. But few people were saying this stuff in 2008.

Yudkowsky said AI would be a problem when very few people taken seriously in the mainstream were saying it was going to be a problem. Saying "specific predictions are wrong" is missing the forest for the trees here.

I was responding to someone who said Yudkowsky was "consistently wrong with all their predictions". Yes, fair enough, Yudkowsky wasn't the literal first person ever to say that AI might be bad. The point was that the common academic response at the time if you were to say AI could be bad was to laugh you out of the room. IMO, you get a lot of points for making a prediction when almost everyone else in the world disagrees with you. The reason those movies you cited were blockbusters was because very view people believed that they were realistic. No one made a movie about a pandemic in 2020.

I don't think there's much to be gained out of hashing out whether every prediction Yudkowsky has said was right or wrong: I likely directionally agree with you there, as I also find some of his more extreme predictions to be inaccurate. I mostly take issue with "consistently wrong". The results in longtermwiki are not "consistently wrong". He's definitely wrong sometimes. But consistently?

The discussion isn't about whether it's an "original or interesting thought", it's about whether Yudkowsky is "consistently wrong with all their predictions". You keep shifting the topic.

We agree the guy roughly said AI will be dangerous. We agree AI is dangerous. Not sure what more there is to say here.

You are saying 1) other people have said the same thing and 2) you don't like the particular way he said it. Those can both be true, but that isn't even close to "consistently wrong with all their predictions".

The guy was saying that AI was going to be a serious problem decades before anyone else was even considering it as a remote possibility. How is that in any way "consistently wrong with all their predictions"?

When your best counter-argument is “you donate money to charity” you have to start wondering if you’re on the bad side and not the good side.

No one says "You are a bad employee" in a perf review because it would be a personal attack. They say things like "when you did X it had Y outcome" because that's a fact, not a personal attack.

So much of the discourse around this on HN is nonsensical, and I fully agree with you. It's patently absurd that Anthropic would demand him to rewrite Bun into Rust; it's equally absurd that they would demand any sort of stunt at all when Anthropic already pulled off the biggest stunt with Bun: running Claude Code on it. And why on earth would you cannibalize the runtime of your golden goose?

This is such a poor mischaracterization of OP that I actually started agreeing with OP more.

Tell me if I am oversimplifying, but I never understood the noise about the two sigma problem. Like, of course if you have a private tutor to immediately answer any question that pops into your head at the immediate moment you get confused, you are going to learn vastly more efficiently than in a large classroom where once you get confused you are likely to stay confused. To say nothing of how the pace will likely either drag way behind what you'd like, or accelerate too fast ahead of it.

The environment is just obviously two sigma better. This just... seems obvious to me? In the same way that I will get stronger much faster if I have a physical trainer to tell me exactly what I am doing wrong when I do it? And it seems obviously unsolvable other than by getting everyone a private tutor (or AI..?).

Asking from a place of curiosity.

When you hear a woosh as the point flies by, I see someone attacking a project for using AI rather than any concrete technical reason. Jared's question is to disentangle an actual Rust-related bug report from someone who likes to complain about AI.

Pretty sure the author of Bun stated this was not related to Bun here on HN.

I don't really get the Bun thing. Bun is running Claude Code which is probably the single most actively used development app there is. You say this was a bad use of LLMs, but it's been in production for a while and I haven't heard of any evidence that Claude Code has increased a significantly larger quantity of errors, segfaults, etc, than before.

That also isn't saying "don't say this is an LLM". If the guidelines didn't want us to say someone is an LLM, it would explicitly say "don't say someone is an LLM". It wouldn't hint at it in an indirect way.

FWIW I do find it somewhat useful to have someone point out "this is an LLM" - I don't always have my AI detector on and I appreciate it when other people do. And when someone says particular text was LLM generated I need to go back and think about whether I believe it a bit harder.

I don’t see anything in there about not commenting on whether the author is using an LLM?

The thing that annoys me most about this obviously AI-generated article is: "The quotes in orange boxes are real and checkable." No they aren't - you AI generated them, just like you generated the rest of the page.

You mean the obviously AI generated README? Did you even read it yourself?

To be blunt I can't take this product seriously when they don't even run benchmarks. Your prompts make Claude better? Cool: prove it. Methods to evaluate LLM performance exist, they're called evals/benchmarks, and every company that is serious about AI runs them when they release a new version. (Of course benchmarks have their own issues, but squabbling over which benchmark is best and what issues there are is step 2 in being a Serious AI Company and step 1 is running them at all!) The fact that the only proof they have that 6 is better than five is a hacky table in a screenshot from Fable is, honestly, concerning.

And Jest was itself a huge step up from what came before (Jasmine, Mocha...)

It's a linter, a code formatter, a tester, and a bundler. What exists in your "boring" stack that's more boring than that?