MurphyA/hacker-news huggingface dataset:
by abdullahkhalids | 2025-07-24 17:23:26+00:00
There exist metrics like ELO or GLIKO that can be used to rate the overall performance of teams. This is usually a good predictor for the overall winrate of a team A. But doesn't predict as well whether A will win against a particular B. This is because there is a lot more going on in particular matchups that is difficult to capture mathematically. It is not uncommon to see A beating B consistently, B beating C consistently, and C beating A consistently.

Perhaps a neural network can be trained on a lot more data to make predictions for each match, and I imagine who gamble a lot have probably done things like this already. But then you don't have a number to optimize.
by norir | 2025-07-24 17:23:37+00:00
It is very unfortunate that we use fixed width numbers by default in most programming languages and that common ops will silently overflow. Smarter compilers can work with richer numeric primitives and either automatically promote machine words to big numbers or throw an error on overflow.

People talk a lot about the productivity gains of ai, but fixing problems like this at the language level could have an even bigger impact on productivity, but are far less sensational. Think about how much productivity is lost due to obscure but detectable bugs like this one. I don't think rust is a good answer (it doesn't check overflow by default), but at least it points a little bit in the vaguely correct direction.
by iLemming | 2025-07-24 17:23:55+00:00
I do know and like F#, and just like the other commenter I think I personally prefer it over some Haskell's ways. F# was my first FP language, I was so excited about it, but it was a hard sell back then to my team of charpers, so I sneaked it in by writing tests in it for an otherwise altogether C# codebase.

Too sad that the dotnet world largely still operates in csharpland and F# unfairly gets ignored even within dotnet community. I never have found a team where F# is preferred over other options, and I'd absolutely love to see what it's like. Unfortunately, F#'s hiring story is far worse than other less popular languages and even if there is anything, you most likely end up supporting other projects in C#, and honestly, even though it's a fine language by many measures, I see C# as "past experience" that I personally am not too eager to try again and do it as my daily job.
by 827a | 2025-07-24 17:24:02+00:00
I disagree entirely, and I can convince you I'm right with one sentence: More lines of JS/TS are written by AI than lines of Rust are written at all. We don't have the data to assert this as true, but I think the vast majority of people would agree with that statement.

This statement being true disproves the statement "the industry has been making huge efforts to push errors from runtime, to compile time." The industry is not a monolith. Different actors have different, individualized goals.
by abalashov | 2025-07-24 17:24:06+00:00
The problem with the "agents" thing is that it's mostly hype, and doesn't reflect any real AI or model advances that makes them possible.

Yes, there's a more streamlined interface to allow them to do things, but that's all it is. You could accomplish the same by copy-and-pasting a bunch of context into the LLM before and asking it what to do. MCP and other agent-enabling data channels now allow it to actually reach out and do that stuff, but this is not in itself a leap forward in capabilities, just in delivery mechanisms.

I'm not saying it's irrelevant or doesn't matter. However, it does seem to me that as we've run out of low-hanging fruit in model advances, the hype machine has pivoted to "agents" and "agentic workflows" as the new VC-whetting sauce to keep the bubble growing.
by AlotOfReading | 2025-07-24 17:24:33+00:00
I was assuming sqlite did the sane thing and used a CRC. CRCs have (limited) error correction capabilities that you can use to fix 1-2 bit errors in most circumstances, but apparently sqlite uses a Fletcher variant and gives up that ability (+ long message length error detection) for negligible performance gains on modern (even embedded) CPUs.
by dijit | 2025-07-24 17:24:45+00:00
It always feels like “this time its different”.

NoOps, NoSQL, Heroku, PaaS, IaaS.

Maybe there are less people in operations than before, there are certainly some companies that do their best not to employ any operations focused people and use FaaS for everything and only hire feature developers… who, end up doing the operations work that crops up.

shrug
by timr | 2025-07-24 17:24:53+00:00
> It's not a bad paper, but it's also turning into a fantastic illustration of how much thirst there is out there for anything that shows that AI productivity doesn't work.

Maybe. I think it's a fantastic illustration of anyone doing anything to provide something other than hype around the subject. An actual RCT? Too good to be true! The thirst is for fact vs. speculation, influencer blogposts and self-promotion.

That this RCT provided evidence opposing the hype, is, of course, irresistible.
by Terr_ | 2025-07-24 17:25:03+00:00
That seems a little reductive to me, since "needs more time" could mean many different things, ex:

1. (Overall rate) From the same starting-point, this child will always require 2x the time/effort to learn than expected.

2. (Overall offset) This child's thresholds for becoming able to learn many skills at the normal rate tends to be 6 months later than expected.

3. (Specific rates) For a particular task this child learned slowly no matter how old they were.

4. (Specific offsets) For a particular task this child learned slowly, but when stopped trying and revisited it X months later they had no problems.

Of those, it sounds like you're assuming the harshest, first version.

I'm no child developmental psychologist, but I'd wager that versions 2,3,4 are more frequent than most people would assume, since they take more work to distinguish and the universe tends to be messy.
by svantana | 2025-07-24 17:25:36+00:00
I don't think it's so clear-cut. The C spec I found is 4MB and the tcc compiler source code is 1.8MB. It might need some more code to be fully compliant, but it may still be smaller than 4MB. I think the main reason why code bases are much larger is because they contain stuff not covered by the spec (optimization, vendor-specific stuff, etc etc).

Personally I'd rather write a compiler than a specification, but to each their own.
by no_wizard | 2025-07-24 17:25:39+00:00
I wish we did a more formal study, but at $previous_job we rolled out AI tools (in that case it was github copilot) and we found that for 6-8 months productivity largely stayed the same or reduced slightly, but after that it sharply increased. This was rolled out to hundreds of developers with training, guidance, support etc. It was done in what I would consider the right way.
by impure | 2025-07-24 17:25:42+00:00
I find it funny that the first sentence is: I’m not sure if the whole AI thing is falling apart, but we are definitely in a phase where the hype doesn’t match what we are seeing in the real world.

Also I do not think AI is falling apart and I do not think the productivity loss is surprising. It's something I've noticed a lot, you have to check AI output line by line thereby making you slower. AI makes tasks easier, not necessarily faster. And because people are lazy and love making things easier it's still going to be adopted no matter what anyone says.
by duxup | 2025-07-24 17:25:47+00:00
>According to the Henley ranking, which is based on the number of destinations a traveler can visit without needing a visa, the United States has fallen from seventh place last year to 10th place, continuing a downward trend. Now tied with Iceland and Lithuania, the U.S. last topped the list in 2014.

The article doesn't seem to indicate what changed, what countries require a visa that didn't used to for the US.
by pydry | 2025-07-24 17:25:57+00:00
ive watched a lot of people code with cursor, etc. and i noticed that they seem to get a rush when it occasionally does something amazing that more than offsets their disappointment when it (more often) screws up.

the psychological effect reminds me a bit of slot machines, which provide you with enough intermittent wins to make you feel like you're winning while youre lose.

I think this might be linked to that study that found experienced oss devs who thought they were faster when they were in actual fact 20% slower.
by roguecoder | 2025-07-24 17:26:52+00:00
* claim to be against

This is about power, not preventing violence.

It is classic 1970s TERF stuff. Dworkin identified real problems, but her solutions are bad and make the actual problems worse by targeting already-targeted people for greater policing. What they do do is give suburbanite women the rush of power and control, building their own little evangelical theocracies.
by cultofmetatron | 2025-07-24 17:27:03+00:00
I was a nodejs engineerfor 7 years previously and had a lot of experience it. if you're building a backend, unless you're relying on a specific library or building a microservice, I think elixir/phoenix is a way better stack. being functional and having a pass by value by default, you avoid whole classes of errors you have to learn to look out for in node. While there was some initual challenge setting up autodiscover with libcluster, it means we were able to get away with not setting up a message queue or pubsub system or websocket infrasturcture since all that came out of the box. Additionally, creating services is as easy as adding a controller in rails. just use Genserver and add it to your supervisor file.

TLDR: sure i could have done it in node but it would have been a LOT more work and less reliable
by haswell | 2025-07-24 17:27:24+00:00
The issue I have with comments like this one is the one-dimensional notion of value described as "productivity gains" for a single person.

There are many things in this world that could be fairly described as "more productive" or "faster" than the norm, yet few people would argue that it makes those things a net benefit. You can lie and cheat your way to success, and that tends to be successful too. There are good reasons society frowns on this.

To me, focusing only on "I'm more productive" while ignoring the systemic and societal factors impacted by that "productivity" is completely missing the forest for the trees.

The fact that you further feel that there isn't even a point in engaging on the topic is disturbing considering those ignored factors.
by infoseekadvice | 2025-07-24 17:27:27+00:00
Fun fact: apparently "hostile" work environment, in the legal sense, doesn't cover things like shouting, or apparently even throwing things if they don't connect with you (!).

So to be honest, it was partly a backdoor way to handle a mishandled harassment issue.

(In addition to refusing to engage in the interactive process, they did not follow their own internal policies on investigating harassment complaints.)

So it was two issues in parallel: One was a harassment issue, the other was some sensory things.

One of the accommodations I asked for was written feedback -- a common one for folks on the spectrum. This made the person angry, since it's hard to say "I told you to do X, why did you do X" when it's in writing instead of a verbal discussion.

Anyways, my goal is to just move on, treat the eventual windfall (they've already tried offering me $ at least once) as if it doesn't exist, and try to keep on doing the work I love -- if it had had a different culture I'd have kept on even if I hit the lottery.

Hence the HN post -- I can't be the first person to be retaliated against, and I'd like to think if I can provide references and point at projects/duties I'd easily be able to move on to a similar role at another company. Aside from the shouting thing, a lot of what I asked for would be met in a hybrid or remote role, since by their nature you need to do a lot of written comms to keep ppl on the same page.
by nickpsecurity | 2025-07-24 17:27:41+00:00
It's worth mentioning because the AI developers have been using alignment training to make AI's see the world through the lens of intersectionality. That ranges from censoring what those philosophies would censor to simply presenting answers like they would. Some models actually got dumber as they prioritized indoctrination as "safety" training. It appears that many employees in the companies think that way, too.

Most of the world, and a huge chunk of America, thinks in different ways. Many are not aware the AI's are being built this way either. So, we want AI's that don't have a philosophy opposite of ours. We'd like them to either be more neutral or customizable to the users' preferences.

Given the current state, the first steps are to reverse the existing trend (eg political fine-tuning) and use open weights we can further customize. Later, maybe purge highly-biased stuff out of training sets when making new models. I find certain keywords, whether liberal or conservative, often hint they're going to push politics.
by dathinab | 2025-07-24 17:27:53+00:00
I think their problem is less about material knowledge to shrink nodes but about development tooling to make chip design more efficient, scalable and allows experimenting with more new approaches/allows larger shifts without planing years ahead for it.

TSMC by collaborating with many different customers with different needs had a lot of insensitive to not just create powerful tooling for one kind of CPU design approach but also being very flexible to allow other approaches for other needs. And AMD has repeatedly interrelated on their whole tool chain and dev. processes for many years while Intel was somewhat complacent with what they had.

And a bunch of the recent issues with CPUs internally dying sound a lot like miss-design issues which tooling should have coughed (instead of looking like fundamental tech/production issues).
by proteal | 2025-07-24 17:28:10+00:00
It’s kinda like why they make compsci majors take a history class - the actual knowledge may not be particularly useful unto itself, but learning that information/skill tickles a part of the brain you dont normally use. So that later, when you need to use your whole brain to solve some problem, all parts of it are strong.

So are the skills themselves important? Not per se, but they represent “meta skills” that we want kids to develop when they are most apt to learn.

Ultimately, I think it’s a big TBD - a child’s mind innately wants to learn, it’s just unclear what kids are learning when exposed to so much tech early on and that’s what has teachers worried. I bet the kids will turn out fine, but we as a society won’t really know until the kids are old enough to tell us firsthand.
by mckngbrd | 2025-07-24 17:28:44+00:00
I had hardly written any code prior to ChatGPT other than teaching myself some VBA.

Since then, using Gen AI tools to learn + write code, I have deployed a functioning full stack application to the web. NextJS on Vercel, with a backend server also deployed running on Python, and a Supabase DB. Is it the best application ever making loads of money? Definitely not. Are there things wrong with it? Absolutely (although I promise I'm not exposing sensitive env vars and API keys to the web). Did the first versions look like absolute ass as I clumsily figured things out and made bad mistakes? You bet. But it's a functioning app that does some useful things and has real users.

I would never have imagined doing this in a million years prior to Gen AI.

Do some devs see mixed results depending on how they're using the tools? I'm sure. Is Gen AI overhyped broadly speaking? Probably so. But when I see people say it's a delusion, waste of resources, and everyone is wasting their time on it ... for me, it just doesn't line up.
by jt2190 | 2025-07-24 17:28:47+00:00
> “I think the economics of it are we have to consider the resiliency of the supply chain, I think we learned that during the pandemic — the idea that you think about your supply chains not just by the lowest cost, but also about reliability, about resiliency, and all those things. I think that’s how we’re thinking about U.S. manufacturing,” [AMD CEO Lia Su] said to Bloomberg’s Ed Ludlow.

This almost sounds verbatim what U.S. Secretary of the Treasury Scott Bessent told Bloomberg yesterday, so take the headline phrase “worth it” in that context.
by afro88 | 2025-07-24 17:28:51+00:00
Sigh, there's that study again, quoted without any "early 2025" context. In early 2025 AI wasn't very effective, especially when used by engineers that didn't have an intuition for what to and what not to use it for.

It's different in mid 2025. The next quote is simonw in mid 2025 saying don't quit engineering. Right now it's as if we're carpenters and the buzz saw was just invented. Shouldn't that be in the first group of quotes?

If you look at his set of quotes through another lens it's saying: Software engineering is changing due to AI. AI wasn't great in early 2025, but recently got a lot better. Some CEOs and plenty of journos are giddy at the possibility of layoffs. Layoffs aren't actually happening though.

That's a far cry from "no one knows anything about AI".
by immibis | 2025-07-24 17:28:54+00:00
TPL: virtual permanent LAN party, closed group.

DN42: build a second internet to learn how it works. Public, no privacy features.

Yggdrasil: build a next generation Internet with some privacy features, and self-organization without central assignment

Tor/I2P: build a completely private internet, but sacrificing speed and the ability to operate on the base layer. (Yggdrasil and DN42 and TPL can run on individual one-to-one links, but Tor and I2P assume existing any-to-any connectivity on the layer beneath, which means you already need an internet)
Show HN: A code editor that integrates into the browser
by quintu5 | 2025-07-24 17:28:54+00:00
When the startup I was working for shut down, I knew it would probably be a while before my health allowed me to commit to a new role, so I decided to start working on some personal projects to keep my mind active and engaged.

With AI-augmented VS Code forks being all the rage at the time, I wanted to take a slightly different angle on a code editor/viewer using the same core technology. That led me to building Tachi Code, a Monaco-based code editor that integrates directly into your browser as an extension to streamline your more ephemeral coding tasks, so you can spend less time switching between your code editor and browser.

The original flow that piqued my interest was viewing raw source files or API responses. Historically, I've used a JSON formatter extension to prettify JSON, but I wanted something more powerful, more universal, and quite frankly, something that looked better, so I built Tachi Code with the ability to detect when you're viewing pre-formatted text and inject itself into the page, so it's always beautifully syntax highlighted, foldable, and regex searchable. Then I added context menu integrations, so you could quickly edit snippets, compare text, or view the current page's source in Tachi Code's editor.

The browser extension works offline with the only external HTTP requests going to GitHub to retrieve JSON Schemas or additional themes. All user data stays local. The only tracking is CloudFlare's web analytics beacon on TachiCode.dev (not present in the browser extension or in the EU).

TachiCode.dev is a sandbox environment that serves the latest commit of Tachi Code's editor hosted on CloudFlare Pages.

The core stack is: - React 19 - Monaco Editor - Radix UI - Zustand - Shiki - WXT (full SBOM is available via the about dialog if you want to dig deeper)

Monaco Editor provides the code and diff editors, as well as low level systems for configuration and theming. There's a lot of hackery involved in surfacing those systems and integrating them into the larger React app. Shiki is used to provide more complete syntax highlighting than Monaco Editor provides out of the box. The rest of the UI is primarily based on Radix UI components, typically starting from a shadcn template and then reworked to use colors provided by the theme system. Zustand is my go-to for any kind of shared/persistent state. WXT just turns browser extension development and publishing into a breeze.

If you've got any feedback or a question about how the app was developed, I'd love to hear it!
by fragmede | 2025-07-24 17:28:56+00:00
At the end of the day Bitcoin is a networked technology. It's worthless to me if you/the store/landlord/taxman won't take it, and most of them don't, so its value is only between adherents, which means, sure, I can buy some, but then what? Use it to buy something sketchy online?

Meanwhile, anyone can go to chat.com and ask for code to do whatever they ask. Some questions it will answer well, others it will not. Because we're discussing this in the abstract, LLM good!/LLM bad! Grar!, and barely touching on details, like the programming language, the libraries, nevermind sharing the prompts, both camps are convinced they're right, with much more furvor than Bitcoin. Additionally the technology is evolving so fast that someone's bad experience from a couple months ago is already out of date. Meanwhile, how many times can you have the same argument about Bitcoin? There are a couple details here and there, but nothing structurally changed with Bitcoin since its inception. Which is a shame, if they'd managed to fork so transactions weren't horribly slow, maybe we'd be having a different discussion. But I digress.

The volume of emotion is different, not because of the money swimming around, of which there is a lot, but because we're arguing over things we see with our own eyes but aren't giving enough detail to have productive discussions about. Insulting people adds to the emotionally charged nature. Things like "If you find LLMs used, it's because you're a bad programmer/an idiot/only work on loser problems" or "AIs going to put you out of a job" don't encourage reasonable nuanced discussion. Insulting someone for liking Bitcoin doesn't cut as deep. No one's been working on Bitcoin for four decades and made it their whole (public) identity.
by umpalumpaaa | 2025-07-24 17:29:00+00:00
100%.

Some more modern languages - eg. Swift – have "sendable" value types that are inherently thread safe. In my experience some developers tend to equate "sendable" / thread safe data structures with a silver bullet. But you still have to think about what you do in a broader sense… You still have to assemble your thread safe data structures in a way that makes sense, you have to identify what "transactions" you have in your mental model and you still have to think about data consistency.
by OldGreenYodaGPT | 2025-07-24 17:29:04+00:00
Honestly, at this point, I'll just work 2 hours a day since I'm already producing 5-10x the output of my coworkers who aren't leveraging Claude Code at the medium-sized startup where I work. It really makes you wonder what's holding people back if they haven't at least doubled their productivity by now
by 0cf8612b2e1e | 2025-07-24 17:29:06+00:00
Let’s pretend that the Apple restriction is 100% effective- how much impact would you expect to Meta’s bottom line? Sure, Meta would love to know every spicy detail of your life, but just following in app activity probably reveals more than enough to sway advertisers.

Meta hoovers up every detail because they can. Knowing that user #7227724 spends 23 minutes a day in Spotify might make the ad targeting 0.4% more accurate, but does not seem like the lynchpin for the entire business.
by stonemetal12 | 2025-07-24 17:29:11+00:00
>AI is important. But we don’t yet fully know why.

And that is how you know it is hype and not actually important. Imagine any other actually important thing then try to add we don't know why. Doctors important but we don't know why. Electric cars important but we don't know why. Computers important but we don't know why. It just doesn't work.