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> Programmers resistance to AI assisted programming has lowered considerably. Even if LLMs make mistakes, the ability of LLMs to deliver useful code and hints i

> Programmers resistance to AI assisted programming has lowered considerably. Even if LLMs make mistakes, the ability of LLMs to deliver useful code and hints improved to the point most skeptics started to use LLMs anyway: now the return on the investment is acceptable for many more folks. I'm not a fan of this phrasing. Use of the terms "resistance" and "skeptics" implies they were wrong. It's important we don't engage in revisionist history that allows people in the future to say "Look at the irrational fear programmers had of AI, which turned out to be wrong!" The change occurred because LLMs are useful for programming in 2025 and the earliest versions weren't for most programmers. It was the technology that changed.

20k 10mo ago
Its also significantly lowered because management is forcing AI on everyone at gunpoint, and saying that you'll lose your job if you don't love AI That's a very easy way to get everyone to pinky promise that they absolutely love AI to the ends of the earth
- deleted 10mo ago
  [deleted]
Aurornis 10mo ago
> The change occurred because LLMs are useful for programming in 2025 But the skeptics and anti-AI commenters are almost as active as ever, even as we enter 2026. The debate about the usefulness of LLMs has grown into almost another culture war topic. I still see a constant stream of anti-AI comments on HN and every other social platform from people who believe the tools are useless, the output is always unusable, people who mock any idea that operator skill has an impact on LLM output, or even claims that LLMs are a fad that will go away. I’m a light LLM user ($20/month plan type of usage) but even when I try to share comments about how I use LLMs or tips I’ve discovered, I get responses full of vitriol and accusations of being a shill.
- zahlman 10mo ago
  It absolutely is culture war. I can easily imagine a less critical version of myself having ended up in that camp. It comes across to me that the perspective is informed by core values and principles surrounding what "intelligence" is. I butted heads with many earlier on, and they did nothing to challenge that frame meaningfully. What did change is my perception of the set of tasks that don't require "intelligence". And the intuition pump for that is pretty easy to start — I didn't suppose that Deep Blue heralded a dawn of true "AI", either, but chess (and now Go) programs have only gotten even more embarrassingly stronger. Even if researchers and puzzle enthusiasts might still find positions that are easier for a human to grok than a computer.
- Hendrikto 10mo ago
  > from people who believe the tools are useless, the output is always unusable, people who mock any idea that operator skill has an impact on LLM output You are attacking a strawman. Almost nobody claims that LLMs are useless or you can never use their output.
  - Aurornis 10mo ago
    Those claims are all throughout this thread and in replies to my comments. It’s not a strawman. It’s everywhere on HN.
    - Hendrikto 10mo ago
      Such as? Currently, the top comments are > LLMs have certainly become extremely useful for Software Engineers > LLMs are useful for programming in 2025 > Do LLMs make bad code: yes all the time (at the moment zero clue about good architecture). Are they still useful: yes, extremely so. If your comment is not a strawman, show me where people actually claim what you say they do.
- otabdeveloper4 10mo ago
  "Useful for programming" is a massive and dishonest bait and switch. Lots of things are "useful for programming". Switching to a comfier chair is more useful for programming than any LLM. We were sold vibe coding, and that's what managers want.
ookblah 10mo ago
you just need to hop into any AI reltaed thread (even this one) and it's pretty clear no one is revising anything, skepticism is there lol.
mjr00 10mo ago
"Skeptics" is also a loaded term; what does it actually mean? I find LLMs incredibly useful for various programming tasks (generating code, searching documentation, and yes with enough setup agents can accomplish some tasks), but I also don't believe they have actual intelligence, nor do I think they will eviscerate programming jobs, the same way that Python and JavaScript didn't eviscerate programming jobs despite lowering the barrier to entry compared to Java or C. Does that make me a skeptic? It's easy to declare "victory" when you're only talking about the maximalist position on one side ("LLMs are totally useless!") vs the minimalist position on the other side ("LLMs can generate useful code"). The AI maximalist position of "AI is going to become superintelligent and make all human work and intelligence obsolete" has certainly not been proven.
- Aurornis 10mo ago
  No, that doesn’t make you a skeptic in this context. The LLM skeptics claim LLM usefulness is an illusion. That the LLMs are a fad, and they produced more problems than they solve. They cite cherry picked announcements showing that LLM usage makes development slower or worse. They opened ChatGPT a couple times a few months ago, asked some questions, and then went “Aha! I knew it was bad!” when they encountered their first bad output instead of trying to work with the LLM to iterate like everyone who gets value out of them. The skeptics are the people in every AI thread claiming LLMs are a fad that will go away when the VC money runs out, that the only reason anyone uses LLMs is because their boss forces them to, or who blame every bug or security announcement on vibecoding.
  - mjr00 10mo ago
    > No, that doesn’t make you a skeptic in this context. That's good to hear, but I have been called an AI skeptic a lot on hn, so not everyone agrees with you! I agree though, there's a certain class of "AI denialism" which pretends that LLMs don't do anything useful, which in almost-2026 is pretty hard to argue.
    - Aurornis 10mo ago
      > That's good to hear, but I have been called an AI skeptic a lot on hn, so not everyone agrees with you! The context was the article quoted, not HN comments. I’ve been called all sorts of things on HN and been accused of everything from being a bot to a corporate shill here. You can find people applying labels and throwing around accusations in every thread here. It doesn’t mean much after a while.
nl 10mo ago
There is some limited truth in this but we still see claims that LLMs are "just next token predictors" and "just regurgitate code they read online". These are just uninformed and wrong views. It's fair to say that these people were (are!) wrong.
- zahlman 10mo ago
  Objecting to these claims is missing their point. Saying these things is really about denying that the LLMs "think" in any meaningful sense. (And the retorts I've seen in those discussions often imply very depressing and self-deprecating views of what it actually means to be human.)
  - emp17344 10mo ago
    Leave it to HN to be militantly misanthropic to sell chatbots.
- mjr00 10mo ago
  > we still see claims that LLMs are "just next token predictors" and "just regurgitate code they read online". These are just uninformed and wrong views. It's fair to say that these people were (are!) wrong. I don't think it's fair to say that at all. How are LLMs not statistical models that predict tokens? It's a big oversimplification but it doesn't seem wrong, the same way that "computers are electricity running through circuits" isn't a wrong statement. And in both cases, those statements are orthogonal to how useful they are.
  - jcelerier 10mo ago
    > How are LLMs not statistical models that predict tokens? there's LLMs as in "the blob of coefficients and graph operations that runs on a gpu whenever there's an inference" which is absolutely "a statistical model that predict tokens" and LLMs as in "the online apps that iterates and have access to an entire automated linux environment that can run $LANGUAGE scripts and do web queries when an intermediary statistical output contains too much maybes and use the result to drive further inference.".
mvkel 10mo ago
One only has to go read the original vibe coding thread[0] from ...ten months ago(!) to see the resistance and skepticism loud and clear. The very first comment couldn't be more loud about it. It was possible to create things in gpt-3.5. The difference now is it aligns with the -taste- of discerning programmers, which has a little, but not everything, to do with technological capability. [0]https://news.ycombinator.com/item?id=42913909 https://news.ycombinator.com/item?id=42913909
- zahlman 10mo ago
  > The difference now is it aligns with the -taste- of discerning programmers This... doesn't match the field reports I've seen here, nor what I've seen from poking around the repos for AI-powered Show HN submissions.
  - mvkel 10mo ago
    On the tabs vs spaces battleground there are no winners; we just need to lower our expectations :)
- HarHarVeryFunny 10mo ago
  "Look Ma, no hands!" vibe coding, as described by Karpathy, where you never look at the code being generated, was never a good idea, and still isn't. Some people are now misusing "vibe coding" to describe any use of LLMs for coding, but there is a world of difference between using LLMs in an intelligent considered way as part of the software development process, and taking a hit on the bong and "vibe coding" another "how many calories in this plate of food" app.
  - mvkel 10mo ago
    Karpathy himself has used "vibe coding" to describe "usage of LLMs for coding," so it's fair to say the definition has expanded. https://karpathy.bearblog.dev/year-in-review-2025/ https://karpathy.bearblog.dev/year-in-review-2025/
    - 10mo ago
HarHarVeryFunny 10mo ago
Yes, it's a strange take. It's not that programmers have changed their mind about unchanging LLMs, but rather that LLMs have changed and are now useful for coding, not just CoPilot autocomplete like the early ones. What changed was the use of RLVR training for programming, resulting in "reasoning" models that are now attempting to optimize for a long-horizon goal (i.e. bias generation towards "reasoning steps" that during training let to a verified reward), as opposed to earlier LLMs where RL was limited to RLHF. So, yeah, the programmers who characterized early pre-RLVR coding models as of limited use were correct. Now the models are trained differently and developers find them much more useful.
- zahlman 10mo ago
  I thought I'd read a lot of these threads this year, and also discussed off-site the use of coding agents and the technology behind them; but this is genuinely the first time I've seen the term "RLVR".
  - HarHarVeryFunny 10mo ago
    RLVR "reinforcement learning for verifiable rewards" refers to RL used to encourage reasoning towards achieving long-horizon goals in areas such as math and programming, where the correctness/desirability of a generated response (or perhaps an individual reasoning step) can be verified in some way. For example generated code can be verified by compiling and running it, or math results verified by comparing to known correct results. The difficulty of using RL more generally to promote reasoning is that in the general case it's hard to define correctness and therefore quantify a reward for the RL training to use.
    - zahlman 10mo ago
      > The difficulty of using RL more generally to promote reasoning is that in the general case it's hard to define correctness and therefore quantify a reward for the RL training to use. Ah, hence the "HF" angle.
      - 10mo ago

20k 10mo ago

Its also significantly lowered because management is forcing AI on everyone at gunpoint, and saying that you'll lose your job if you don't love AI That's a very easy way to get everyone to pinky promise that they absolutely love AI to the ends of the earth

deleted 10mo ago
[deleted]

Aurornis 10mo ago

> The change occurred because LLMs are useful for programming in 2025 But the skeptics and anti-AI commenters are almost as active as ever, even as we enter 2026. The debate about the usefulness of LLMs has grown into almost another culture war topic. I still see a constant stream of anti-AI comments on HN and every other social platform from people who believe the tools are useless, the output is always unusable, people who mock any idea that operator skill has an impact on LLM output, or even claims that LLMs are a fad that will go away. I’m a light LLM user ($20/month plan type of usage) but even when I try to share comments about how I use LLMs or tips I’ve discovered, I get responses full of vitriol and accusations of being a shill.

zahlman 10mo ago
It absolutely is culture war. I can easily imagine a less critical version of myself having ended up in that camp. It comes across to me that the perspective is informed by core values and principles surrounding what "intelligence" is. I butted heads with many earlier on, and they did nothing to challenge that frame meaningfully. What did change is my perception of the set of tasks that don't require "intelligence". And the intuition pump for that is pretty easy to start — I didn't suppose that Deep Blue heralded a dawn of true "AI", either, but chess (and now Go) programs have only gotten even more embarrassingly stronger. Even if researchers and puzzle enthusiasts might still find positions that are easier for a human to grok than a computer.
Hendrikto 10mo ago
> from people who believe the tools are useless, the output is always unusable, people who mock any idea that operator skill has an impact on LLM output You are attacking a strawman. Almost nobody claims that LLMs are useless or you can never use their output.
- Aurornis 10mo ago
  Those claims are all throughout this thread and in replies to my comments. It’s not a strawman. It’s everywhere on HN.
  - Hendrikto 10mo ago
    Such as? Currently, the top comments are > LLMs have certainly become extremely useful for Software Engineers > LLMs are useful for programming in 2025 > Do LLMs make bad code: yes all the time (at the moment zero clue about good architecture). Are they still useful: yes, extremely so. If your comment is not a strawman, show me where people actually claim what you say they do.
otabdeveloper4 10mo ago
"Useful for programming" is a massive and dishonest bait and switch. Lots of things are "useful for programming". Switching to a comfier chair is more useful for programming than any LLM. We were sold vibe coding, and that's what managers want.

ookblah 10mo ago

you just need to hop into any AI reltaed thread (even this one) and it's pretty clear no one is revising anything, skepticism is there lol.

mjr00 10mo ago

"Skeptics" is also a loaded term; what does it actually mean? I find LLMs incredibly useful for various programming tasks (generating code, searching documentation, and yes with enough setup agents can accomplish some tasks), but I also don't believe they have actual intelligence, nor do I think they will eviscerate programming jobs, the same way that Python and JavaScript didn't eviscerate programming jobs despite lowering the barrier to entry compared to Java or C. Does that make me a skeptic? It's easy to declare "victory" when you're only talking about the maximalist position on one side ("LLMs are totally useless!") vs the minimalist position on the other side ("LLMs can generate useful code"). The AI maximalist position of "AI is going to become superintelligent and make all human work and intelligence obsolete" has certainly not been proven.

Aurornis 10mo ago
No, that doesn’t make you a skeptic in this context. The LLM skeptics claim LLM usefulness is an illusion. That the LLMs are a fad, and they produced more problems than they solve. They cite cherry picked announcements showing that LLM usage makes development slower or worse. They opened ChatGPT a couple times a few months ago, asked some questions, and then went “Aha! I knew it was bad!” when they encountered their first bad output instead of trying to work with the LLM to iterate like everyone who gets value out of them. The skeptics are the people in every AI thread claiming LLMs are a fad that will go away when the VC money runs out, that the only reason anyone uses LLMs is because their boss forces them to, or who blame every bug or security announcement on vibecoding.
- mjr00 10mo ago
  > No, that doesn’t make you a skeptic in this context. That's good to hear, but I have been called an AI skeptic a lot on hn, so not everyone agrees with you! I agree though, there's a certain class of "AI denialism" which pretends that LLMs don't do anything useful, which in almost-2026 is pretty hard to argue.
  - Aurornis 10mo ago
    > That's good to hear, but I have been called an AI skeptic a lot on hn, so not everyone agrees with you! The context was the article quoted, not HN comments. I’ve been called all sorts of things on HN and been accused of everything from being a bot to a corporate shill here. You can find people applying labels and throwing around accusations in every thread here. It doesn’t mean much after a while.

nl 10mo ago

There is some limited truth in this but we still see claims that LLMs are "just next token predictors" and "just regurgitate code they read online". These are just uninformed and wrong views. It's fair to say that these people were (are!) wrong.

zahlman 10mo ago
Objecting to these claims is missing their point. Saying these things is really about denying that the LLMs "think" in any meaningful sense. (And the retorts I've seen in those discussions often imply very depressing and self-deprecating views of what it actually means to be human.)
- emp17344 10mo ago
  Leave it to HN to be militantly misanthropic to sell chatbots.
mjr00 10mo ago
> we still see claims that LLMs are "just next token predictors" and "just regurgitate code they read online". These are just uninformed and wrong views. It's fair to say that these people were (are!) wrong. I don't think it's fair to say that at all. How are LLMs not statistical models that predict tokens? It's a big oversimplification but it doesn't seem wrong, the same way that "computers are electricity running through circuits" isn't a wrong statement. And in both cases, those statements are orthogonal to how useful they are.
- jcelerier 10mo ago
  > How are LLMs not statistical models that predict tokens? there's LLMs as in "the blob of coefficients and graph operations that runs on a gpu whenever there's an inference" which is absolutely "a statistical model that predict tokens" and LLMs as in "the online apps that iterates and have access to an entire automated linux environment that can run $LANGUAGE scripts and do web queries when an intermediary statistical output contains too much maybes and use the result to drive further inference.".

mvkel 10mo ago

One only has to go read the original vibe coding thread[0] from ...ten months ago(!) to see the resistance and skepticism loud and clear. The very first comment couldn't be more loud about it. It was possible to create things in gpt-3.5. The difference now is it aligns with the -taste- of discerning programmers, which has a little, but not everything, to do with technological capability. [0]https://news.ycombinator.com/item?id=42913909 https://news.ycombinator.com/item?id=42913909

zahlman 10mo ago
> The difference now is it aligns with the -taste- of discerning programmers This... doesn't match the field reports I've seen here, nor what I've seen from poking around the repos for AI-powered Show HN submissions.
- mvkel 10mo ago
  On the tabs vs spaces battleground there are no winners; we just need to lower our expectations :)
HarHarVeryFunny 10mo ago
"Look Ma, no hands!" vibe coding, as described by Karpathy, where you never look at the code being generated, was never a good idea, and still isn't. Some people are now misusing "vibe coding" to describe any use of LLMs for coding, but there is a world of difference between using LLMs in an intelligent considered way as part of the software development process, and taking a hit on the bong and "vibe coding" another "how many calories in this plate of food" app.
- mvkel 10mo ago
  Karpathy himself has used "vibe coding" to describe "usage of LLMs for coding," so it's fair to say the definition has expanded. https://karpathy.bearblog.dev/year-in-review-2025/ https://karpathy.bearblog.dev/year-in-review-2025/
  - 10mo ago

HarHarVeryFunny 10mo ago

Yes, it's a strange take. It's not that programmers have changed their mind about unchanging LLMs, but rather that LLMs have changed and are now useful for coding, not just CoPilot autocomplete like the early ones. What changed was the use of RLVR training for programming, resulting in "reasoning" models that are now attempting to optimize for a long-horizon goal (i.e. bias generation towards "reasoning steps" that during training let to a verified reward), as opposed to earlier LLMs where RL was limited to RLHF. So, yeah, the programmers who characterized early pre-RLVR coding models as of limited use were correct. Now the models are trained differently and developers find them much more useful.

zahlman 10mo ago
I thought I'd read a lot of these threads this year, and also discussed off-site the use of coding agents and the technology behind them; but this is genuinely the first time I've seen the term "RLVR".
- HarHarVeryFunny 10mo ago
  RLVR "reinforcement learning for verifiable rewards" refers to RL used to encourage reasoning towards achieving long-horizon goals in areas such as math and programming, where the correctness/desirability of a generated response (or perhaps an individual reasoning step) can be verified in some way. For example generated code can be verified by compiling and running it, or math results verified by comparing to known correct results. The difficulty of using RL more generally to promote reasoning is that in the general case it's hard to define correctness and therefore quantify a reward for the RL training to use.
  - zahlman 10mo ago
    > The difficulty of using RL more generally to promote reasoning is that in the general case it's hard to define correctness and therefore quantify a reward for the RL training to use. Ah, hence the "HF" angle.
    - 10mo ago