MurphyA/hacker-news huggingface dataset:
by sussmannbaka | 2025-10-14 13:07:26+00:00
this is definitely closer to what I had in mind but it's still rather useless because it just shows what winning the lottery is like. what I am really looking for is neither the "Claude oneshot this" nor the "I gave up and wrote everything by hand" case but a realistic, "dirty" day-to-day work example. I wouldn't even mind if it was a long video (though some commentary would be nice in that case).
by ACCount37 | 2025-10-14 13:08:27+00:00
Off the top of my head: the user wants LLM to help him solve a word puzzle. Think something a bit like Wordle, but less represented in its dataset.

For that, the LLM needs to be able to compare words character by character reliably. And to do that, it needs at least one of: be able to fully resolve the tokens to characters internally within one pass, know to emit the candidate words in a "1 character = 1 token" fashion and then compare that, or know that it should defer to tool calls and do that.

An LLM trained for better tokenization-awareness would be able to do that. The one that wasn't could fall into weird non-humanlike failures.
by grues-dinner | 2025-10-14 13:08:34+00:00
What would quantum technology actually deliver?

Other than collapsing the internet when every pre-quantum algorithm is broken (nice jobs for the engineers who need to scramble to fix everything, I guess) and even more uncrackable comms for the military. Drug and chemistry discovery could improve a lot?

And to be quite honest, the prospect of a massive biotech revolution is downright scary rather than exciting to me because AI might be able to convince a teenager to shoot up a school now and then, but, say, generally-available protein synthesis capability means nutters could print their own prions.

Better healthcare technology in particular would be nice, but rather like food, the problem is that we already can provide it at a high standard to most people and choose not to.
by bangaroo | 2025-10-14 13:08:41+00:00
"it's better at coding" is not useful information, sorry. i'd love to hear tangible ways it's actually better. does it still succumb to coding itself in circles, taking multiple dependencies to accomplish the same task, applying inconsistent, outdated, or non-idiomatic patterns for your codebase? has compliance with claude.md files and the like actually improved? what is the round trip time like on these improvements - do you have to have a long conversation to arrive at a simple result? does it still talk itself into loops where it keeps solving and unsolving the same problems? when you ask it to work through a complex refactor, does it still just randomly give up somewhere in the middle and decide there's nothing left to do? does it still sometimes attempt to run processes that aren't self-terminating to monitor their output and hang for upwards of ten minutes?

my experience with claude and its ilk are that they are insanely impressive in greenfield projects and collapse in legacy codebases quickly. they can be a force multiplier in the hands of someone who actually knows what they're doing, i think, but the evidence of that even is pretty shaky: https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...

the pitch that "if i describe the task perfectly in absolute detail it will accomplish it correctly 80% of the time" doesn't appeal to me as a particularly compelling justification for the level of investment we're seeing. actually writing the code is the simplest part of my job. if i've done all the thinking already, i can just write the code. there's very little need for me to then filter that through a computer with an overly-verbose description of what i want.

as for your search results issue: i don't entirely disagree that google is unusable, but having switched to kagi... again, i'm not sure the order of magnitude of complexity of searching via an LLM is justified? maybe i'm just old, but i like a list of documents presented without much editorializing. google has been a user-hostile product for a long time, and its particularly recent quality collapse has been well-documented, but this seems a lot more a story of "a tool we relied on has gotten measurably worse" and not a story of "this tool is meaningfully better at accomplishing the same task." i'll hand it to chatgpt/claude that they are about as effective as google was at directing me to the right thing circa a decade ago, when it was still a functional product - but that brings me back to the point that "man, this is a lot of investment and expense to arrive at the same result way more indirectly."
by Gualdrapo | 2025-10-14 13:08:46+00:00
SEEKING WORK | Remote

Location: Bogotá, Colombia Remote: Yes Willing to relocate: No Technologies: HTML, CSS, JavaScript, SVG, TeX/ConTeXt, PHP, Jekyll Portfolio: https://miler.codeberg.page/ Résumé-CV: https://codeberg.org/miler/curriculum-vitae/raw/branch/main/curriculum-en.pdf Email: Please see Portfolio or CV/Résumé GitHub: https://github.com/acidrums4/

Professional graphic designer with experience in both frontend and backend (PHP; Wordpress, Framer, some Joomla and some Typo3), iconography, editorial design/typesetting with ConTeXt and general graphic design. Please feel free to check my portfolio for some examples of my work.
by lotsofpulp | 2025-10-14 13:09:34+00:00
Part of it is a hidden tax on the young and workers, by making currency less valuable (what young people and workers have, the ability to earn cash) and transferring that wealth to old people and asset owners (to pay for pensions and healthcare).

That is why mortgages are (future) taxpayer subsidized. Without the subsidies from the future, the real estate prices would not be able to rise so much.

There is also economic agglomeration to exacerbate the issue.
by okaleniuk | 2025-10-14 13:10:06+00:00
Most of the startups actually plan to survive for more than 2 months. And it makes total sense to think about scalability, reliability, and performance while it's still possible to change your whole stack every other week. Not forgetting about other things such as securing your cash flow, growing your talent pool, protecting your IP, etc. Finding a good balance between multiple focii is exactly the job for a founder. Of course, it's a hard job, that's why we don't see many successful startups to begin with.
by qezz | 2025-10-14 13:10:27+00:00
> And guess what? They hate the HCL too.

Don't want to sound too harsh, but to me HCL is even worse than plain YAML.

By expressiveness, HCL is somewhat similar to Ansible-flavoured YAML - in both you need to use magic keywords to create any kind of abstraction (e.g. a loop).

HCL is worse than regular YAML because there's only one "true" parser for it, that is official Hashicorp's HCL parser. So if you are locked into Golang ecosystem, then sure it can work for you, otherwise you are out of luck.

There are a couple of tools that convert HCL into JSON, I tried both, they somewhat work, but in the end of the day it's a big hack. At that point I just gave up on using HCL and started using something else that generates JSON.

Hope you find some configuration layer that fits your users more than HCL or YAML.
by JKCalhoun | 2025-10-14 13:10:43+00:00
Apple was giving away the Keys to the Kingdom by way of licensing Macintosh clones, among other things. If ATG were responsible for hemorrhaging cash I am not sure why they did not re-appear then when Apple was firing on all cylinders. Only Jony was crowned.

And there's no way the library and its books were a cost — unless perhaps it was attracting snooty engineers who were reading Foley and van Dam when they should have been fixing bugs. ;-) (That actually might have been me.)
by andrewlgood | 2025-10-14 13:11:04+00:00
Silly argument. Everything in gravitational physics goes back to Newton? Who cares about Convex Optimization if you do not undertand gravity? Math goes back to Euclid and the Greeks?

Mankind has consistently built upon existing knowledge. "If I have seen further, it is by standing on the shoulders of giants. (Newton)"

IMHO, what we are seeing is the US was generating 50% of the world's GDP at the end of World War II. In that era it could afford to many non-economical things - Marshall Plan, funding research at universities, etc. The US is no longer the dominant economic engine. It actually has to prioritize its spending. Money spent on research is money not spent on food stamps, housing the homeless, defense.

What is never mentioned in these discussions is how much money has been spent on research that did nothing. Advanced nothing. When that is factored in, what is the ROI of university-based research?
by ArnoVW | 2025-10-14 13:11:37+00:00
update on NRC (Dutch newspaper), based on pieces that have been submitted to the courts

https://www.nrc.nl/nieuws/2025/10/14/chinese-topman-gebruikt...

The Chinese CEO of Nexperia, Wing, tried to divert company funds to finance his own chip factory, WingSkySemi, appointing straw men to key positions and firing European executives, which led to a major internal conflict.
by bookofjoe | 2025-10-14 13:11:50+00:00
>How is Peerlist different from LinkedIn?

Peerlist is a community for all tech professionals, especially designers and developers. The platform is built with tech professionals in mind, offering a comprehensive profile to showcase your work across the internet—whether it's projects, open-source contributions, design work, or more.

Peerlist emphasizes a community-driven experience, promoting knowledge sharing, collaboration, and credibility among tech professionals. It also ensures authenticity with verified accounts, making it a more niche and purposeful space compared to LinkedIn's broader, generalist approach.

>What is a Peerlist profile & why do I need one?

Your work might be spread across GitHub, Dribbble, Medium, and other platforms. Peerlist brings everything together into one profile with seamless integrations. You can also highlight your verified work experience, education, and bootcamp credentials in the Resume section, write articles, and showcase your interests—all on a single page.

So when applying for jobs, you only need to share your Peerlist profile.
by ericcurtin | 2025-10-14 13:11:57+00:00
Hi everyone, we're the maintainers.

We're rebooting the model-runner community and wanted to share what we've been up to and where we're headed.

When we first built this, the idea was simple: make running local models as easy as running containers. You get a consistent interface to download and run models from different backends (llama.cpp being a key one) and can even transport them using familiar OCI registries like Docker Hub.

Recently, we've invested a lot of effort into making it a true community project. A few highlights:

- The project is now a monorepo, making it much easier for new contributors to find their way around.

- We've added Vulkan support to open things up for AMD and other non-NVIDIA GPUs.

- We made sure we have day-0 support for the latest NVIDIA DGX hardware.
Show HN: Daily install trends of AI coding extensions in VS Code
by AznHisoka | 2025-10-14 13:12:00+00:00
For the past 4 years, I've been tracking the install counts of AI coding extensions in the Visual Studio Code marketplace (GitHub Copilot, Claude Code, OpenAI Codex, etc.)

Today, I built an interactive dashboard that lets you see daily install counts for any of them over time.

The chart shows GitHub Copilot by default, and you can overlay or swap in any of the other 20+ tools to compare. You can also see important dates in each tool's history (pricing changes, major releases, etc.) and how daily installs changed around those dates.

Important caveats:

1) This only tracks VS Code extension installs, not CLI usage or other IDEs like JetBrains.

2) Cursor isn't included since it's a standalone editor (VS Code fork), not a marketplace extension. I added a second chart showing Cursor discussion forum activity as a proxy for its growth.

Obviously not apples to apples, but felt I needed to measure Cursor's growth somehow.

3) This tracks daily installs per day, NOT total installs. Otherwise the charts would be boring and always go to the top and right.

4) The dashboard was coded using an AI coding assistant too. I used regular Claude :)
Microsoft Is Retiring Project Online in 2026
by trustedit | 2025-10-14 13:12:01+00:00
Microsoft announced that Project Online will reach end-of-life on September 30, 2026. It’s being retired due to its legacy architecture and replaced by newer tools like Microsoft Planner, Project for the Web, and Power Platform. For organizations that rely on Project Online, this means a full migration and possibly rebuilding workflows and reports from scratch. Curious how teams are approaching this — anyone already testing Power Platform for project management?
by happymellon | 2025-10-14 13:12:17+00:00
> I feel like someone who is explicitly leaving windows for Linux by that point would understand it can’t run everything windows does right?

I get it, but it's unfortunately not true.

The amount of folks I've seen complain about their Windows pirate copy of Photoshop CS6 not working on Linux so they will go to Mac over the years has been quite silly.
by timcobb | 2025-10-14 13:12:21+00:00
> what prompted this post? well just tried to work with gpt5 and gemini pro

That's the problem. GPT5, at least in Cursor, doesn't work for coding. It burns tokens and does actually nothing my in experience. Claude 3.5, 4 and 4.5, on the other hand, are pretty solid and make lots of forward progress with minimal instruction. It takes iteration, some skill, some critical thinking, and some hand coding! Yes, LLMs forget things and do random things sometimes, but for me it's a big boost.
by tchojnacki | 2025-10-14 13:12:38+00:00
Location: Poland Remote: Yes Willing to relocate: No Technologies: React, TypeScript, Python, Rust, Astro, Tailwind, JavaScript, CSS, HTML Résumé/CV: https://tchojnacki.dev/cv.pdf Email: tomaszchojnacki2001@gmail.com

I'm a graduate software engineer with a strong focus on front-end development in React and TypeScript, backed by full-stack experience in Python, Rust, Node.js, and databases. I hold a master's degree in applied computer science. During my internship at Atlassian, I shipped production features to Jira, helping improve an app used by 300 000 teams worldwide. As a freelance developer, I collaborated directly with clients to design, build, and deploy websites that attract over 1 000 monthly users.
by sgarland | 2025-10-14 13:13:15+00:00
> Giving other teams the ability to develop their own service without needing to conform to your archaic grey beard architecture restrictions

IME at many different SaaS companies, the only one that had serious reliability was the one that had “archaic grey beard architecture restrictions.” Devs want to use New Shiny X? Put a formal request before the architectural review committee; they’ll read it, then explain how what the team wants already exists in a different form.

I don’t know why so many developers - notably, not system design experts, nor having any background in infrastructure - think that they know better than the gray beards. They’ve seen some shit.

> and your lack of understanding what a pod is or how to get your logs from your cloud.

No one said the gray beards don’t know this. At the aforementioned company, we ran hybrid on-prem and AWS, and our product was hybrid K8s and traditional Linux services.

Re: cloud logs, every time I’ve needed logs, it has consistently been faster for me to ssh onto the instance (assuming it wasn’t ephemeral) and use ripgrep. If I don’t know where the logs were emitted from, I’ll find that first, then ssh. The only LaaS I’ve used that was worth a damn was Sumologic, but I have no idea how they are now, as that was years ago.
by CaptainOfCoit | 2025-10-14 13:13:18+00:00
> None of this is particularly difficult technically. Even simply slapping x509 certs on calls and having some basic filtering would achieve a lot.

Slapping x509 certs on probably some of the oldest telecommunications infrastructure in the world (both in terms of devices using it, and devices enabling it) wouldn't be "technically difficult"?

But I've never worked in telecommunications, maybe I'm overestimating how large piece of work this would be.
by emddudley | 2025-10-14 13:14:26+00:00
Pyrefly vs. ty: Comparing Python’s Two New Rust-Based Type Checkers (2025-05-27) https://blog.edward-li.com/tech/comparing-pyrefly-vs-ty/

HN discussion of above: https://news.ycombinator.com/item?id=44107655

How Well Do New Python Type Checkers Conform? A Deep Dive into Ty, Pyrefly, and Zuban (2025-08-29) https://sinon.github.io/future-python-type-checkers/
by chriswarbo | 2025-10-14 13:14:39+00:00
Env vars are unordered name=value pairs, so are suited for such data.

In contrast, arguments are an ordered sequence of strings, so are more suited for present/not-present flags (e.g. --dry-run) , or listing a variable number of values (e.g. filenames). Using arguments for name=value data either requires individual strings to be parsed into components, or requires a pair of name and value strings to appear sequentially (without overlapping another pair, etc.). Arguments also tend to require disambiguation, e.g. prepending names with `--`, to account for optional arguments not being present, or for allowing options to be given in any order, etc. That may also require escape hatches, like a standalone `--` argument, in case user data conflicts with such reserved patterns, etc.

Sure, there are libraries for parsing this stuff; and conventions that we can get used to (except when a tool doesn't follow them...), but it's still a complicated mess compared to `NAME1=val1 NAME2=val2 my-command --flag1 --flag2 file1 file2 file3`
by GuB-42 | 2025-10-14 13:14:46+00:00
Yes, but ideas are (mostly) worthless. I mean, they are necessary, but that's the easy part, building the technical foundation that make it possible is the hard part.

The internet needs wires and routers, distributed computing need a good network (i.e. the internet), current-day AI needs GPUs and GPUs need silicon chips that defy the laws of physics. Really, looking at the EUV lithography process makes all of computer science feel insignifiant by comparison, everything about it is absurd.

The real progress is that now, we can implement the ideas from the 70s, the good ones at least. I don't want to diminish the work of the founders of computer science, there is real genius here, but out of the billions of people on this planet, individual geniuses are not in short supply, but the real progress come from the millions of people that worked on the industrial complex, supply chains and trade that lead to modern GPUs, among everything that define modern computing.
by ben_w | 2025-10-14 13:15:13+00:00
> unless you are doing something silly, it's difficult to run into CPU speed limitations.

Yes, but it's not difficult to do something silly without even noticing until too late. Implicitly (and unintentionally) calling something with the wrong big-O, for example.

That said, anyone know what's up with the slow deletion of Safari history? Clearly O(n), but as shown in this blog post still only deleted at a rate of 22 items in 10 seconds: https://benwheatley.github.io/blog/2025/06/19-15.56.44.html
by JKCalhoun | 2025-10-14 13:15:43+00:00
I could be putting too fine a point on it, but my impression was that he was kind of jealous of "academia". Not only did he not graduate from but even seemed to eschew higher learning. And to be sure he would have had a harder time bullshitting an expert in a given domain. They had a kind of power of knowledge that he lacked.

At the same time he was clearly enamored with Avadis, very much the academic — appeared to be grooming him for role of Apple CEO. He must have been very disappointed when Avadis left the fold.
by pawelkobojek | 2025-10-14 13:16:19+00:00
I love the speed advantage of pyrefly over (based)pyright but so far it doesn't seem to highlight as much as pyright does, for example it doesn't catch unreachable code like this:

def fn(x: str): if x is None: x = "123" # pyright flags that as unreachable code, pyrefly does not

Autocomplete for modules also doesn't work for me yet:

import os os. # I'll get `ABC, `Any`, `AnyStr`, `AnyStr_co`, `BinaryIO`, ...

Looking forward to have a fast language server for python though, pyright is way too slow for large projects.
by comrade1234 | 2025-10-14 13:16:52+00:00
I live in Switzerland and 10-years-ago I spent about a week in Shanghai and a week in Nanjing. The air in Shanghai was as clean as anything here. The cars, delivery trucks, even the mopeds were all electric.

The week in Nanjing was quite different. Every day you could smell and taste coal smoke and by the end of the day when you blew your nose it came out black. So I assume they were producing electricity with coal far away to make electricity for Shanghai.

It's ten yers later now and from reading about all of the green power they're adding and about installing long-distance power lines to the cities hopefully it allows Nanjing to clean up.
by sgarland | 2025-10-14 13:17:27+00:00
I wouldn’t start with K8s, and I’ve administered it at multiple companies. Unless every one of your initial hires is a SWE turned SRE, you’re in for a bad time (and you don’t need it).

I’d personally start with Linux services on some VMs, but Docker Compose is also valid. There are plenty of wrappers around Compose to add features if you’d like.
by spaceman_2020 | 2025-10-14 13:17:35+00:00
The wheels are being sold to humans sitting inside their houses who have been told that if they have enough wheels on the road, they will make the world more productive. Meanwhile, the wheelmaker loses money on every wheel but gets money from the rubber factory. And the rubber factory gets money by selling its stock to the humans sitting inside their houses.

But yes, a lot of wheels are being sold. For now
by nyeah | 2025-10-14 13:18:28+00:00
I'm talking about how equity works at the most basic level, in a vehicle worth 1000 USD. It's an ice cream stand, capisce?

You may well be offended because we were rude to each other. That's fair. But you're not telling me to stop being a dick. You're telling me my ice cream stand has to be listed on a major US stock exchange. That's not a strong argument, and it's not really on topic.
by bluGill | 2025-10-14 13:18:41+00:00
Human factors studies on programming languages are really hard to do right. It is easy to study someone seeing a language for the first time. However programming well requires a high level of expertise and so the real question isn't how easy it is for a beginner, it is how easy it is for someone who has been doing it for years. Or maybe how much different is someone after a week vs month vs year (that is at what point do the experience gains plateau)- in all this you have to be careful to ask different tasks - since good programmers will abstract when they need to do something twice.
by __MatrixMan__ | 2025-10-14 13:18:42+00:00
Once you figure out how to get your model to go find the context it needs (for me this usually comes down to really good error messages that feel a bit like a prompt injection attack) and you figure out how to keep the tasks small and uniform-ish such that a passing test for a previous (supervised) task becomes a reason that that output can now be used as context for how to complete the next (unsupervised) task, agents can be pretty darn reliable.

Maybe 50% of the problems we solve are repetitive enough for this to make sense, and 50% of those are unpredictable enough that a model in a loop isn't overkill compared to traditional automation, and 50% of those are too small to be worth investing in the necessary scaffolding. But if you're looking at a problem that's in that magical 12.5%, a properly constrained agent is absolutely the way to go.