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Reflections on AI at the End of 2025

antirez.com

191–200 of 383 posts

Re: Reflections on AI at the End of 2025

#191

Earlier quoted context omitted.

Skeptic here: I do think LLMs are a fad for software development . They're an interesting phenomen that people have convinced themselves MUST BE USEFUL in the context of software development, either through ignorance or a sense of desperation. I do not believe LLMs will be used long term for any kind of serious software development use cases, as the maintenance cost of the code they produce will run development teams…

In this year of 2025, in December, I find it untenable for anyone to hold this position unless they have not yet given LLMs a good enough try. They're undeniably useful in software development, particularly on tasks that are amenable to structured software development methodologies. I've fixed countless bugs in a tiny fraction of the time, entirely accelerated by the use of LLM agents. I get the most reliable results…

You're on the internet, you can make whatever claims you want. But even with no sources or experimental data, you can always add some rational logic to add weight to your claims.

> They're undeniably useful in software development

> I've fixed countless bugs in a tiny fraction of the time

> I get the most reliable results

> This works extremely well and reliably in producing high quality results.

If there's one common thing in comments that seems to be astroturfing for LLM usage, it's that they use lots of superlative adjectives in just one paragraphs.

Re: Reflections on AI at the End of 2025

#192

> 1. NOT have any representation about the meaning of the prompt. This one is bizarre, if true (I'm not convinced it is). The entire purpose of the attention mechanism in the transformer architecture is to build this representation, in many layers (conceptually: in many layers of abstraction ). > 2. NOT have any representation about what they were going to say. The only place for this to go is in the model weights. M…

> This one is bizarre, if true (I'm not convinced it is). > The entire purpose of the attention mechanism in the transformer architecture is to build this representation, in many layers (conceptually: in many layers of abstraction). I think this is really about a hidden (i.e. not readily communicated) difference in what the word "meaning" means to different people.

Could be, by "meaning" I mean (heh) that transformers are able to distinguish tokens (and prompts) in a consequential ("causal") way, and that they do so at various levels of detail ("abstractions").

I think that's the usual understanding of how transformer architectures work, at the level of math.

Re: Reflections on AI at the End of 2025

#193

Earlier quoted context omitted.

Skeptic here: I do think LLMs are a fad for software development . They're an interesting phenomen that people have convinced themselves MUST BE USEFUL in the context of software development, either through ignorance or a sense of desperation. I do not believe LLMs will be used long term for any kind of serious software development use cases, as the maintenance cost of the code they produce will run development teams…

> They're an interesting phenomen that people have convinced themselves MUST BE USEFUL in the context of software development, Reading these comments during this period of history is interesting because a lot of us actually have found ways to make them useful, acknowledging that they’re not perfect. It’s surreal to read claims from people who insist we’re just deluding ourselves, despite seeing the results Yeah they’…

It's absolutely possible to be mistaken about this. The placebo effect is very strong. I'm sure there are countless things in my own workflow that feel like a huge boon to me while being a wash at best in reality. The classic keyboard vs. mouse study comes to mind: https://news.ycombinator.com/item?id=2657135

This is why it's so important to have data. So far I have not seen any evidence of a 'Cambrian explosion' or 'industrial revolution' in software.

Re: Reflections on AI at the End of 2025

#194
post #135

Earlier quoted context omitted.

> 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.

On the other hand, ever since LLMs came on the scene, there’s been a vocal group claiming that AI will become intelligent and rapidly bring about human extinction - think the r/singularity crowd. This seems just as untenable a position to hold at this point. It’s becoming clear that these things are simply tools. Useful in many cases, but that’s it.

> This seems just as untenable a position to hold at this point

To say that any prediction about the future shape of a technology is 'untenable' is pretty silly. Unless you've popped back in a time machine to post this.

Re: Reflections on AI at the End of 2025

#195
Regarding the stochastic parrots:

It is easy to see that LLMs exclusively parrot by asking them about current political topics [1], because they cannot plagiarize settled history from Wikipedia and Britannica.

But of course there also is the equivalence between LLMs and Markov chains. As far as I can see, it does not rely on absurd equivalences like encoding all possible output states in an infinite Markov chain:

https://arxiv.org/abs/2410.02724

Then there is stochastic parrot research:

https://arxiv.org/abs/2502.08946

"The stochastic parrot phenomenon is present in LLMs, as they fail on our grid task but can describe and recognize the same concepts well in natural language."

As said above, this is obvious to anyone who has interacted with LLMs. Most researchers know what is expected of them if they want to get funding and will not research the obvious too deeply.

[1] They have Internet access of course.

Re: Reflections on AI at the End of 2025

#196

Earlier quoted context omitted.

>> So the number of anti-vaxxers is going to plummet drastically in the following decade, I guess. > Depends if they use lobotomized bots like Grok... What are you on about? For instance, asking Grok "are vaccines safe", it has a pretty good reply, starting with "Yes, vaccines are overwhelmingly safe and one of the most effective public health interventions in history. Extensive scientific evidence from decades of re…

The issue is what happens when @catturd2 quotes this and tweets Elon about Grok not toeing the party line about vaccines

[deleted]

Re: Reflections on AI at the End of 2025

#197
post #22

> And I've vibe coded entire ephemeral apps just to find a single bug because why not - code is suddenly free, ephemeral, malleable, discardable after single use. Vibe coding will terraform software and alter job descriptions. I'm not super up-to-date on all that's happening in AI-land, but in this quote I can find something that most techno-enthusiast seem to have decided to ignore: no, code is not free. There are i…

Can you provide numbers relative to things many of us already do? - drive to the store or to work - take a shower - eat meat - fly on vacation And so on... thanks!

Of those things you mention, I only take showers (but not even everyday). But maybe I’m an outlier.

Re: Reflections on AI at the End of 2025

#198
post #190

Earlier quoted context omitted.

> but this won’t work in any non-trivial case Earlier this year google shared that one of their projects (I think it was alphaevolve) found an optimisation in their stack that sped up their real world training runs by 1%. As we're talking about google here, we can be pretty sure it wasn't some trivial python trick that they missed. Anyhow, at ~100M$ / training run, that's a 1M$ save right there. Each and every time t…

The second example has nothing to do with the first. I am optimistic that LLMs are great for translations with good testing frameworks. “Optimize” in a vacuum is a tarpit for an LLM agent today, in my view. The Google case is interesting but 1% while significant at Google scale doesn’t move the needle much in terms of statistical significance. It would be more interesting to see the exact operation and the speed up a…

Why do you think it's not relevant to the "optimise in a loop" thing? The way I think of it, it's using LLMs "in a loop" to move something from arch A (that costs x$) to arch B (that costs y$), where y is cheaper than x. It's still an autonomous optimisation done by LLMs, no?

Re: Reflections on AI at the End of 2025

#199
Practical question: when getting the AI to teach you something, eg how attention can be focused in LLMs, how do you know it’s teaching you correct theory? Can I use a metric of internal consistency, repeatedly querying it and other models with a summary of my understanding? What do you all do?

Re: Reflections on AI at the End of 2025

#200

Earlier quoted context omitted.

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…

Skeptic here: I do think LLMs are a fad for software development . They're an interesting phenomen that people have convinced themselves MUST BE USEFUL in the context of software development, either through ignorance or a sense of desperation. I do not believe LLMs will be used long term for any kind of serious software development use cases, as the maintenance cost of the code they produce will run development teams…

Thanks for articulating this position. I disagree with it, but it is similar to the position I held in late 2024. But as antirez says in TFA, things changed in 2025, and so I changed my mind ("the facts change, I change my opinions"...). LLMs and coding agents got very good about 6 months ago and myself and a lot of other seasoned engineers I respect finally starting using them seriously.

For what it's worth:

* I agree with you that LLMs probably aren't a path to AGI.

* I would add that I think we're in a big investment bubble that is going to pop, which will create a huge mess and perhaps a recession.

* I am very concerned about the effects of LLMs in wider society.

* I'm sad about the reduced prospects for talented new CS grads and other entry-level engineers in this world, although sometimes AI is just used as an excuse to paper over macroeconomic reasons for not hiring, like the end of ZIRP.

* I even agree with you that LLMs will lead to some maintenance nightmares in the industry. They amplify engineers' ability to produce code, and there a lot of bad engineers out there, as we all know: plenty of cowboys/cowgirls who will ship as much slop as they can get away with. They shipped unmaintainable mess before, they will ship three times as much now. I think we need to be very careful.

But, if you are an experienced engineer who is willing to be disciplined and careful with your AI tools, they can absolutely be a benefit to your workflow. It's not easy: you have to move up and down a ladder of how much you rely on the tool, from true vide coding for throwaway use-once helper scripts for some dev or admin task with a verifiable answer, all the way up to hand-crafting critical business logic and only using the agent to review it and to try and break your implementation.

You may still be right that they will create a lot of problems for the industry. I think the ideal situation for using AI coding agents is at a small startup where all the devs are top-notch, have many years of experience, care about their craft, and hold each other to a high standard. Very very few workplaces are that. But some are, and they will reap big benefits. Other places may indeed drown in slop, if they have a critical mass of bad engineers hammering on the AI button and no guard-rails to stop them.

This topic arouses strong reactions: in another thread, someone accused me of "magical thinking" and "AI-induced psychosis" for claiming precisely what TFA says in the first paragraph: that LLMs in 2025 aren't the stochastic parrots of 2023. And I thought I held a pretty middle of the road position on all this: I detest AI hype and I try to acknowledge the downsides as well as the benefits. I think we all need to move past the hype and the dug-in AI hate and take these tools seriously, so we can identify the serious questions amidst the noise.

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