Claude is good at assembling blocks, but still falls apart at creating them

Post by baq » Fri, Jan 16, 2026, 6:02 AM UTC

filoeleven wrote: post #147

nextaccountic wrote: post #131

Earlier quoted context omitted.

Then you apply LLMs in domains where things can be checked Indeed I expect to see a huge push into formally verified software just because sound mathematical proofs provide an excellent verifier to put into a LLM hardness. Just see how Aristotle has been successful at math, and it could be applied to coding too Maybe Lean will become the new Python https://harmonic.fun/news#blog-post-verina-bench-sota

"LLMs reliably fail at abstraction." "This limitation will go away soon." "Hallucinations haven't." "I found a workaround for that." "That doesn't work for most things." "Then don't use LLMs for most things."

Post by baq » Fri, Jan 16, 2026, 6:12 AM UTC

irishcoffee wrote: post #150

soulofmischief wrote: post #125

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That's wonderful, but you are ignoring that your kid comes built in with a massive range of biological priors, built by millions of years of evolution, which make counting natural and easy out of the box. Machine learning models have to learn all of these things from scratch. And does your child's understanding of mathematics scale? I'm sure your 4-year-old would fail at harder arithmetic. Can they also tell me why 1…

I hope you restore your energy, I had no idea this was so exhausting! Truly, I'll stop afflicting my projected lack of knowledge, sorry I tired you out!

Post by baq » Fri, Jan 16, 2026, 6:25 AM UTC

imiric wrote: post #73

lordnacho wrote: post #64

By and large, I agree with the article. Claude is great and fast at doing low level dev work. Getting the syntax right in some complicated mechanism, executing an edit-execute-readlog loop, making multi file edits. This is exactly why I love it. It's smart enough to do my donkey work. I've revisited the idea that typing speed doesn't matter for programmers. I think it's still an odd thing to judge a candidate on, but…

> Being able to type quickly and accurately reduces LLMs can generate code quickly. But there's no guarantee that it's syntactically, let alone semantically, accurate. > I feel that I'm learning faster because I'm not tripping over silly little things. I'm curious: what have you actually learned from using LLMs to generate code for you? My experience is completely the opposite. I learn nothing from running generated…

Post by measurablefunc » Fri, Jan 16, 2026, 6:27 AM UTC

danpalmer wrote: post #153

measurablefunc wrote: post #152

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This is the right answer. Unless there is some equivalent of it on the open internet which their search engine can find you should not expect a good outcome.

"good outcome" is pretty subjective, I do get useful productivity gains from some LLM work, but the issues are the same as they always have been.

Post by Jensson » Fri, Jan 16, 2026, 7:07 AM UTC

TeMPOraL wrote: post #136

atty wrote: post #118

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I think both your statement and their statement are too strong. There is no reason to think LLMs can do everything a human can do, which seems to be your implication. On the other hand, the technology is still improving, so maybe it’ll get there.

My take is that: 1) LLMs cannot do everything humans can, but 2) There's no fundamental reason preventing some future technology to do everything humans can, and 3) LLMs are explicitly designed and trained to mimic human capabilities in fully general sense . Point 2) is the "or else magic exists" bit; point 3) says you need a more specific reason to justify assertion that LLMs can't create new concepts/abstractions,…