MurphyA/hacker-news huggingface dataset:
by adrian_b | 2025-10-14 08:00:07+00:00
China has the right to protest, because nowadays the Chinese companies are not "subjected to the same type of treatment".

There is a huge difference between establishing from the beginning clear rules that set limits to foreign investment, like in China, and changing the rules afterwards, after luring foreign investors, and then taking ownership of their assets, like for Tik Tok and Nexperia.

Obviously I agree that USA and the EU have acted very foolishly in the past by exporting technology to China (foolishly for the national interests, while a few have been greatly enriched by this), but at least they followed consistent policies, not like now, when they change the rules of the game whenever they see that they are the losers.

Philips Semiconductors should have never been sold and become non-Dutch, but if they have been so stupid as to do this, they should assume their responsibility and finance the creation of a new European semiconductor device manufacturer, to ensure the independence of hostile entities.
by leptons | 2025-10-14 08:00:19+00:00
In my experience it depends on which way the wind is blowing, random chance, and a lot of luck.

For example, I was working on the same kind of change across a few dozen files. The prompt input didn't change, the work didn't change, but the "AI" got it wrong as often as it got it right. So was I "using it wrong" or was the "AI" doing it wrong half the time? I tried several "AI" offerings and they all had similar results. Ultimately, the "AI" wasted as much time as it saved me.
by deadfoxygrandpa | 2025-10-14 08:00:44+00:00
thats not true. in most manufacturing industries we produce fewer units than we did 20 or 30 years ago, and in most of those industries the total value produced has been pretty flat. this is something a lot of economists have known about all along. you can read about it here:

https://www.palladiummag.com/2025/10/03/how-gdp-hides-indust...
by pjmlp | 2025-10-14 08:01:36+00:00
While those languages made the concepts mainstream, they weren't the ones coming up with them.

Rust's "ownership model", is a simplification of Cyclone, AT&T's research on a better C, based on mix of affine and linear type systems.

https://en.wikipedia.org/wiki/Cyclone_(programming_language)

Haskell's "Lazy evaluation" was present in Miranda, before all related researchers came up with Haskell as common playground.

https://en.wikipedia.org/wiki/Miranda_(programming_language)

"History of Haskell"

https://www.microsoft.com/en-us/research/wp-content/uploads/...

Java's "Green threads" go back to systems like Concurrent Pascal.

https://dl.acm.org/doi/10.1145/775332.775335
by lmm | 2025-10-14 08:02:03+00:00
> There’s simply no such thing as a free market. Why we single out subsidy as non free is arbitrary. What activities constitute legitimate free market behavior? There’s no actual logically sound distinction.

Sounds like a nirvana fallacy. Yes, nowhere has a perfectly free market, just as nowhere has a perfectly corruptionless justice system and railroad tracks are never perfectly parallel. But there are definitely markets that are less free than others and actions that distort markets further, and it's right to call those out.
by fabian2k | 2025-10-14 08:02:05+00:00
For me, a big issue is that the performance of the AI tools varies enormously for different tasks. And it's not that predictable when it will fail, which does lead to quite a bit of wasted time. And while having more experience prompting a particular tool is likely to help here, it's still frustrating.

There is a bit of overlap for the stuff you use agents and the stuff that AI is good at. Like generating a bunch of boilerplate for a new thing from scratch. That makes the agent mode more convenient for me to interact with AI for the stuff it's useful in my case. But my experience with these tools is still quite limited.
by 1718627440 | 2025-10-14 08:02:17+00:00
Having this in the editor leads to people removing that information from other channels. For example class properties are now often coloured, so people do not name or refer to them to denote that they are not some random other variable. I don't like this, because I think all information should be in the code itself and it can be really annoying once you work and haven't your favorite editor available in the correct setup.
by tovej | 2025-10-14 08:02:55+00:00
I would say they can't reliably deliver simple work. They often can, but reliability, to me, means I can expect it to work every time. Or at least as much as any other software tool, with failure rates somewhere in the vicinity of 1 in 10^5, 1 in 10^6. LLMs fail on the order of 1 in 10 times for simple work. And rarely succeed for complex work.

That is not reliable, that's the opposite of reliable.
by atwrk | 2025-10-14 08:03:10+00:00
> It is not falsifiable because it is not a hypothesis but a framework for recognizing science.

And if the source of that framework is not (part of your definition of) science, how do we know whether that framework is true?

That was sort of my point: Poppers criterion is nice, but only works for a small subset of (natural) science - and even there has to face criticism because it is simply too naive for many edge cases.
by aosaigh | 2025-10-14 08:03:34+00:00
> Unfortunately, nobody wanted to buy these even for a cost that would cover all the expenses spent on this project. On the bright side, I have learned a lot, plus, I have a cool PS2 to play with

I'm not sure if the OP is here, but the other obvious way to cover costs here is to create Youtube videos of the restoration process. I love these (as do lots of other people).

One of my favourites is a power-tool repair technician in Ireland:

https://www.youtube.com/@deandohertygreaser
by chainofthought | 2025-10-14 08:03:43+00:00
I'm always prompting. I let Gemini calendar my time (Google Calendar, of course) so that there are zero gaps where unwanted human thought could sneak in. I use an agent manager called Pelican to check in with all of my agents every second and have them tell me what I should be working on next using meta-agents, which are agents running tools in a loop to run tools in a loop. It's super effective!
by Perenti | 2025-10-14 08:03:46+00:00
I use my phone on average 5m per week. This week is bigger, due to lots of medical things. I've spent 3m on it today as of 6pm.

No social media. No videos. No Music. I don't click on links in texts except the one that will show me where my taxi is.

At restaurants people around me sit together with food going cold on plates whilst staring at their phones. People walk around and into me whilst staring at their phones. I saw someone nearly step on a nesting Bush Stone Curlew, despite the protests from the bird's mate, because they were staring at their phone.

I do not believe we are cognitively capable of dealing with interruptions that demand our attention every 30 seconds. I know that despite a long list of life threatening illnesses I am the least anxious person I know, and I think that everyone else is stressing because they are staring at their phone.

* Anecdote, one person's experience. YMMV
Ask HN: Which cross platform desktop GUI to use instead of Electron?
by tones411 | 2025-10-14 08:03:54+00:00
Electron gets hate due to filesize and memory bloat. C++ gets hate for memory leaks. Rust with Tauri relies on a webview which could change versions underneath the app when the OS gets an update.

Which language and cross platform desktop GUI framework checks the boxes for being lightweight in terms of filesize and memory usage, has native controls, supports accessibility and uses retained mode rendering, and works the same ten years from now as the day it was installed?

If someone were to build an installable desktop app with buttons, checkboxes, inputs etc. (so not a video game) which language and GUI framework should they to use to please the memory and filesize conscious?
by varun_chopra | 2025-10-14 08:04:43+00:00
Marketing is being done really well in 2025, with brands injecting themselves into conversations on Reddit, LinkedIn, and every other public forum. [1]

CEOs, AI "thought leaders," and VCs are advertising LLMs as magic, and tools like v0 and Lovable as the next big thing. Every response from leaders is some variation of https://www.youtube.com/watch?v=w61d-NBqafM

On the ground, we know that creating CLAUDE.md or cursorrules basically does nothing. It’s up to the LLM to follow instructions, and it does so based on RNG as far as I can tell. I have very simple, basic rules set up that are never followed. This leads me to believe everyone posting on that thread on Cursor is an amateur.

Beyond this, if you’re working on novel code, LLMs are absolutely horrible at doing anything. A lot of assumptions are made, non-existent libraries are used, and agents are just great at using tokens to generate no tangible result whatsoever.

I’m at a stage where I use LLMs the same way I would use speech-to-text (code) - telling the LLM exactly what I want, what files it should consider, and it adds _some_ value by thinking of edge cases I might’ve missed, best practices I’m unaware of, and writing better grammar than I do.

Edit:

[1] To add to this, any time you use search or Perplexity or what have you, the results come from all this marketing garbage being pumped into the internet by marketing teams.
by nebula8804 | 2025-10-14 08:04:52+00:00
>I can say with some confidence that an alcoholic Fox News talk show host is not smarter than me.

Well he was valedictorian at his high school and graduated from Princeton University. I wonder if the Pete Hegseth from Princeton is the same Pete Hegseth today. I don't know, maybe he got messed up somehow during one of his three tours overseas serving in the military.
by miroljub | 2025-10-14 08:05:01+00:00
I said I won't answer anymore, but your lies and allegations can't stay unanswered.

No, you were unable to understand. It's not about me, I never mentioned my rights. I don't even live in a country that pretends to have free speech protection.

It's you who invents lies about me, twists my words, and then criticizes me for something that you said I claimed. It's petty and manipulative. Your above comment shows one more time what kind of person you are.
by thundoe | 2025-10-14 08:05:08+00:00
Unless AGI includes a speed requirement, AGI is not sufficient to win the market. Take any genius in human history, the impact they had has been hugely limited by their lifespan, they didn’t solve every problem, and each discovery took them decades. The first AGIs will be the same, hyper slow for a while, giving competitors a chance to copy and stay in the race
by pjmlp | 2025-10-14 08:06:14+00:00
I never got why.

I use Python since version 1.6, mainly for OS scripting, because I rather use something with JIT/AOT in the box for application software.

Still, having a little setup script to change environment variables for PYTHONPATH, PATH and a few other things, always did the trick.

Never got to spend hours tracking down problems caused by the multiple solutions that are supposed to solve Python's problems.
by mschuster91 | 2025-10-14 08:06:51+00:00
Because there is a lot of money tied up in AI now, in a way that doesn't just reek like a bubble waiting to implode but even more stinks like a bunch of what used to be called "wash trading" [1]. And that's just the money side.

The "social kool-aid" side is even worse. A lot of very rich and very influential people have bet their career on AI - especially large companies who just outright fired staff to be replaced both by actual AI and "Actually Indians" [2] and are now putting insane pressure on their underlings and vendors to make something that at least looks on the surface like the promised AI dreams of getting rid of humans.

Both in combination explains why there is so much half-baked barely tested garbage (or to use the term du jour: slop) being pushed out and force fed to end users, despite clearly not being ready for prime time. And on top of that, the Pareto principle also works for AI - most of what's being pushed is now "good enough" for 80%, and everyone is trying to claim and sell that the missing 20% (that would require a lot of work and probably a fundamentally new architecture other than RNG-based LLMs) don't matter.

[1] https://www.bbc.com/news/articles/cz69qy760weo

[2] https://www.osnews.com/story/142488/ai-coding-chatbot-funded...
by ninetyninenine | 2025-10-14 08:07:08+00:00
It’s because people are using different tiers of AI and different models. And many people don’t stick with it long enough to get a more nuanced outlook of AI.

Take Joe. Joe sticks with AI and uses it to build an entire project. Hundreds of prompts. Versus your average HNer who thinks he’s the greatest programmer in the company and thinks he doesn’t need AI but tries it anyway. Then AI fails and fulfills his confirmation bias and he never tries it again.
by bob1029 | 2025-10-14 08:08:28+00:00
> If the machine shop is so tightly constrained and error-phobic

Isn't the entire point of a machine shop to be these things?

> capacity in hardware manufacturing has rotted away to the point where things are hanging on by a thread.

You cannot make a profit on a manufacturing line that is not being utilized. Keeping spare tools around and functional just in case is very expensive insurance policy.

Semiconductor manufacturing follows these rules as aggressively as possible. The entire line is built based on the speed of the highest cost tools. There are cases where having redundant tooling would definitely prevent some scrap events, but the premium on this options contract is never worth it on average.
by joshvince | 2025-10-14 08:09:00+00:00
> if you’re working on novel code, LLMs are absolutely horrible

This is spot on. Current state-of-the-art models are, in my experience, very good at writing boilerplate code or very simple architecture especially in projects or frameworks where there are extremely well-known opinionated patterns (MVC especially).

What they are genuinely impressive at is parsing through large amounts of information to find something (eg: in a codebase, or in stack traces, or in logs). But this hype machine of 'agents creating entire codebases' is surely just smoke and mirrors - at least for now.
by berkes | 2025-10-14 08:09:09+00:00
And some more variations that, in my anecdotal experience make or break the agentic experience:

* strictness of the result - a personal blog entry vs a complex migration to reform a production database of a large, critical system

* team constraints - style guides, peer review, linting, test requirements, TDD, etc

* language, frameworks - quick node-js app vs a java monolyth e.g.

* legacy - a 12+ year Django app vs a greenfield rust microservice

* context - complex, historical, nonsensical business constraints and flows vs a simple crud action

* example body - a simple crud TODO in PHP or JS, done a million times vs a event-sourced, hexagonal architecrtured, cryptographical signing system for govt data.
by gwd | 2025-10-14 08:09:27+00:00
Exactly one of two things is true:

1. The tool is capable of doing more than OP has been able to make it do

2. The tool is not capable of doing more than OP has been able to make it do.

If #1 is true, then... he must be using it wrong. OP specifically said:

> Please pour in your responses please. I really want to see how many people believe in agentic and are using it successfully

So, he's specifically asking people to tell him how to use it "right".
by smt88 | 2025-10-14 08:09:34+00:00
I sometimes meet devs who are "using it wrong" with under-baked prompts.

But mostly my experience is that people who regularly get good output from AI coding tools fall into these buckets:

A) Very limited scope (e.g. single, simple method with defined input/output in context)

B) Aren't experienced enough in the target domain to see the problems with the AI's output (let's call this "slop blindness")

C) Use AI to force multiple iterations of the same prompt to "shake out the bugs" automatically instead of using the dev's time

I don't see many cases outside of this.
by johncoltrane | 2025-10-14 08:09:35+00:00
The ones you can find online are sold by people who know the market all too well so the prices are high. Plus it's online so there's no guarantee about anything.

Pawn shops, thrift stores, or their "modern" equivalents (EasyCash, CashConverters, etc. YMMV) would be a good start. I got mine out of a pile for 10€ at a countryside GiFi (French store) ten years ago.
by WA | 2025-10-14 08:10:59+00:00
Another theory: you have some spec in your mind, write down most of it and expect the LLM to implement it according to the spec. The result will be objectively a deviation from the spec.

Some developers will either retrospectively change the spec in their head or are basically fine with the slight deviation. Other developers will be disappointed, because the LLM didn't deliver on the spec they clearly hold in their head.

It's a bit like a psychological false memory effect where you misremember and/or some people are more flexibel in their expectations and accept "close enough" while others won't accept this.

At least, I noticed both behaviors in myself.
by atoav | 2025-10-14 08:11:03+00:00
Yeah makes sense, with docker in the mix the things uv brings are less interesting, although using uv for small one-off scripts is also an interesting application (there is a way of making uv your shebang, declaring sependencies within the python file and essentially getting a uv-ran python script that will auto-download the needed dependencies).

Over the years I encountered many situations where other solutions (pip+pyenv, poetry, easy_install) lead to hour long stops in dependency hell. Meanwhile uv just works. Even the most complicated projects I transfered over since I decided to make the switch worked first try.

I am not the person who has to go for the newest shiniest thing just because, but if that new shiny thing does the job instead of wasting my time sign me up.
by hansmayer | 2025-10-14 08:11:08+00:00
The answer is really trivial and really embarrassingly simple, once you remove the engineering/functional/world improvement goggles. The answer is: because the rich folks invested a ton of money and they need it to work. Or at least to make most of the white collar work dependent on it, quality be damned. Hence the ever increasing pushing, nudging, advertising, offering to use the crap-tech everywhere. It seems now it will not win over the engineers. Unfortunately it seems to work with most of the general population. Every lazy recruiter out there is now using chatgpt to generate job summaries and "evaluate" candidates. Every "office worker" of the general type deadweight you meet at every company is happy to use it to produce more powerpoints, slides and documents for you drown in. And I won't even mention the "content" business model of the influencers.
by zwnow | 2025-10-14 08:11:24+00:00
Exactly, the actual business value is way smaller people think and its honestly frustrating. Yes they can write boilerplate, yes they sometimes do better than humans in well understood areas. But its negligible considering all the huge issues that come with them. Big tech vendorlocks, data poisoning, unverifiable information, death of authenticity, death of creativity, ignorance of LLM evangelists, power hungriness in a time where humanity should look at how to decrease emissions, theft of original human work, theft of data big tech gets away with since way too long. Its puzzling to me how people actually think this is a net benefit to humanity.
by DiogenesKynikos | 2025-10-14 08:12:55+00:00
> And more than half the phones in Europe or America are Asian - what's your point?

Actually, the US banned the most successful Chinese phone company the second it started gaining market share. At the time, it was the largest phone brand in Europe.

But my point is that European and American companies can and do invest and do business in China, on a massive scale.
by ta1243 | 2025-10-14 08:13:24+00:00
I don't understand why Americans require machines to count. Dumping the ballots into a room and having dozens of people counting them while under the watch of all sorts of interested parties scales perfectly well.

For president you have a piece of paper with two boxes on. You don't even have ranked voting.

Mark an X next to one and put it in a ballot box. Works fine everywhere else.
by simonw | 2025-10-14 08:13:25+00:00
I think the opposite is much more likely to be true: that vendors who charge money for inference are charging more than it costs them to service a prompt.

I've heard from sources that I trust that both AWS and Google Gemini charge more than it costs them in energy to run inference.

You can get a good estimate for the truth here by considering open weight models. It's possible to determine exactly how much energy it costs to serve DeepSeek V3.2 Exp, since that model is open weight. So run that calculation, then take a look at how much providers are charging to serve it and see if they are likely operating at a loss.

Here are some prices for that particular model: https://openrouter.ai/deepseek/deepseek-v3.2-exp/providers
by rcxdude | 2025-10-14 08:13:46+00:00
I am generally against the brainless insistence on just writing tests without thinking about the value vs cost (especially on unit tests, which are usually the lowest value and highest cost IMO), but I have found them extremely valuable on occasion. Sometimes for being able to hammer some bit of tricky code through a bunch of different scenarios while figuring out the edge cases, others for validating top-level requirements, and especially for helping prevent regressions while making other changes (which will 100% happen once you have more than one person working on a more than trivial codebase).
by anupsingh123 | 2025-10-14 08:13:50+00:00
Yes, I built 7 AI agents for copying any website. The goal is to create production-quality copies. You can sign up and give it a try! I'm still refining these agents, but first I'm trying to add restrictions so they don't burn through my wallet lol

I started this project out of frustration. When I tried to clone other projects using Claude Code and customize them a bit—simple Next.js, ECS, CDK, and Express server setups—it took several hours just to get everything working. I realized that while vibe coding is great, it's still time-consuming to build a production-ready, functioning product.
by lnrd | 2025-10-14 08:14:05+00:00
> I think what we should really ask ourselves is: “Why do LLM experiences vary so much among developers?”

My hypothesis is that developers work on different things and while these models might work very well for some domains (react components?) they will fail quickly in others (embedded?). So one one side we have developers working on X (LLM good at it) claiming that it will revolutionize development forever and the other side we have developers working on Y (LLM bad at it) claiming that it's just a fad.