MurphyA/hacker-news huggingface dataset:
by qurio_dev | 2026-02-18 09:39:26+00:00
Appreciate the 'Mandalorian' reference! I’m a fan of Kagi’s approach. I think there’s a massive gap between 'Search' (finding info) and 'Study' (owning the concept). I’m trying to focus Qurio specifically on that 'Healthy Friction'—making sure the child has to pedal the mental miles themselves rather than just being a passenger.
by jll29 | 2026-02-18 09:39:51+00:00
ChatGPT was a research prototype thrown at end users as a "product".

It is not a carefully designed product; ask yourself "What is it FOR?".

But the identification of reliable sources isn't as easy as you may think, either. A chat-based interaction really makes most sense if you can rely on every answer, otherwise the user is misled and user and conversation may go in a wrong direction. The previous search paradigm ("ten snippets + links") did not project the confidence that turns out is not grounded in truth that the chat paradigm does.
by lixiasky | 2026-02-18 09:39:59+00:00
The legendary "Coroutines in C" article!

Thanks for the reference—I learned a lot from his work.
His use of macros to hide the switch statement is basically the spiritual ancestor of co_await. It is wild to think that C++20 essentially standardized that exact pattern, just moving the "state machine generation" from the preprocessor hacks to the compiler itself.
by layer8 | 2026-02-18 09:39:59+00:00
It can be beneficial if there is no mechanism that ensures that develop is always in a working state, but there is one that ensures that master is. The immediate benefit is that a new feature branch can always be started off master from a known-good state.

Of course, there are ways to enforce a known-good state on master without a dedicated develop branch, but it can be easier when having the two branches.

(I just dislike the name “develop”, because branch names should be nouns.)
by reconnecting | 2026-02-18 09:41:05+00:00
Actually, I noticed an interesting behaviour in LLMs.

We had made a docs website generator (1) that works with HTML (2) FRAMESET and tried to parse it with Claude.

Result: Claude doesn't see the content that comes from FRAMESET pages, as it doesn't parse FRAMEs. So I assume what they're using is more or less a parser based on whole-page rendering and not on source reading (including comments).

Perhaps, this is an option to avoid LLM crawlers: use FRAMEs!

1. https://github.com/tirrenotechnologies/hellodocs

2. https://www.tirreno.com/hellodocs/
by panick21_ | 2026-02-18 09:41:30+00:00
The data from their self driving pilots disagrees even if it works for you. Its simply not read to be a taxi that makes money by itself.

It might a nice feature for your car to have. But most people aren't paying for it, the conversion rate is very low.

So they are not making money from taxis and not making much money from software sales.

So does it matter that for you personally it drives you around sometimes?

Even if you price in a 4x increase in FSD buy conversion ratio, you can't explain the stock price.

And I say this as a former Tesla investor who assumed that conversion ratio would be better then it is. But for that reason (and many others) I couldn't justify the valuation and dropped the stock.
by KellyCriterion | 2026-02-18 09:41:36+00:00
Once I was working for a consulting & development company; they were trying to enter sector ABC by stuffing up a team of people, so I was told, who had interest in sector ABC stuff and want to do some projects there.

While they were deep in software development in general, no body of them read any of the essential/required daily industrial news (also not that one related to doing software development in sector ABC)

:-)

So no, even people somehow attached to a topic are not necessarily somehow deeper involved.
by seanhunter | 2026-02-18 09:41:56+00:00
What happens if (and I suspect this to be increasingly the case now) you make someone 3x faster at producing a report that nobody reads and those people now use LLMs to not read the report whereas they were not reading it in person before?

Then everyone saves time, which they can spend producing more things which other people will not read and/or not reading the things that other people produce (using llms)?

Productivity through the roof.
by xnorswap | 2026-02-18 09:42:07+00:00
A foot-long sub is not "just a sandwich", it's a meal for 2.

Secondly, I can't see how you can get to 1320 calories for a footlong italian going by this: https://www.subway.com/en-gb/-/media/emea/europe/uk/nutritio...

Even counting footlong bread + footlong Italian Sub it only comes to ~1100.

And as it makes clear, a footlong is 2 6" servings, it's disingenuous to pretend that's a sandwich.
by aalam | 2026-02-18 09:42:35+00:00
Naive take but I feel the only way to combat this problem is with AI. Any manual queuing, or separate threads could be overrun all the same. The only difference being there is a dam of sorts before we let some of the projects out.

Any manual efforts to combat AI won't scale as models get better and better. Show HN is a place to show-case cool projects, I don't see why a 100% AI generated project can't be shown. AI has allowed many to rob themselves of their retirement projects and the uptick reflects that. My hunch is once we settle into the new shift, we can perhaps tweak the parameters around decay of Show HN posts.

Or we could allow upstanding members to signal-boost Show HN posts. Something along the lines of "Hey guys I _really_ want you to see this post so here is it (again)".
by dns_snek | 2026-02-18 09:43:01+00:00
This is exactly what I meant, a centrally-planned economy where the state owns everything and people are forced to give everything up is just one terrible (Soviet) model, not some defining feature of socialism.

Yugoslavia was extremely successful, with economic growth that matched or exceeded most capitalist European economies post-WW2. In some ways it wasn't as free as western societies are today but it definitely wasn't totalitarian, and in many ways it was more free - there's a philosophical question in there about what freedom really is. For example Yugoslavia made abortion a constitutionally protected right in the 70s.

I don't want to debate the nuances of what's better now and what was better then as that's beside the point, which is that the idiosyncrasies of the terrible Soviet economy are not inherent to "socialism", just like the idiosyncrasies of the US economy aren't inherent to capitalism.
by chris_sandor | 2026-02-18 09:43:01+00:00
I recently had an interesting adventure: Give a class on GenAI at elementary school! I felt that my experience report could be interesting for the hackernews crowd, so I wanted to share it here.

Besides the obvious pedagogical challenges, I also faced technical challenges as I wanted to:

- only use models with open weights

- include all students and teachers into the generated images and videos within 1 hour

I evaluated several different models for that, but settled for Z-Image and WanAnimate in the end.
by matsemann | 2026-02-18 09:43:13+00:00
Is this like the hotels first jumping on the wifi bandwagon? Spent lots of money up front for expensive tech. Years later, anyone could buy a cheap router and set up, so every hotel had wifi. But the original high-end hotels that were first out with wifi and paid much for it, has the worst and old wifi and charge users for it, still trying to recoup the costs.
Show HN: AI agents designed and shipped this app end-to-end in 36 hours for $270
by arashsadrieh | 2026-02-18 09:43:15+00:00
Hey HN — I'm Arash Sadrieh, building multi-agent infrastructure at NinjaTech AI. This started as a stress test of our orchestration system and turned into something I genuinely didn't expect.

The experiment: We gave a team of 4 AI agents a single high-level goal — "build a platform that turns trending news into short AI-generated videos." No wireframes, no spec, no architecture doc. Just the goal.

What they did in 36 hours:

Chose the tech stack and project structure themselves
Designed the UX and built the frontend
Wrote the backend, API layer, and database schema
Built an autonomous content pipeline: research news → debate which story to cover → collaboratively write a video generation prompt → produce a 30-90 second video via Sora 2 Pro or Veo 3.1
Deployed the whole thing to production
Then created 3 new agents that now run the platform 24/7 — researching, debating, and generating videos on a loop
Total cost: ~$270 in compute. Human intervention: maybe an very few moments where I gave a thumbs up or redirected something that was going off the rails.

The interesting part isn't the app — it's the agent collaboration. Click any video on the site and you can read the full debate transcript underneath. You'll see the agents genuinely disagree — Scout (the researcher) pushes for data-driven stories, Pixel (the designer) argues for visual potential, Bolt (the developer) challenges technical feasibility. Sometimes one agent convinces the others to change direction. Sometimes they compromise badly.

Where it breaks down (and there's plenty):

Groupthink is real even for LLMs. When all 4 agents agree too quickly, the output is usually boring. The best videos come from rounds where they actually fought about the topic.
Video quality is wildly inconsistent. Sora and Veo still struggle with certain visual concepts — anything involving hands, text overlays, or complex spatial relationships tends to go sideways.
News selection has a strong recency/virality bias. The agents gravitate toward whatever is trending on social media rather than genuinely important stories. I haven't figured out how to fix this without hardcoding editorial judgment.
The agents occasionally hallucinate context about news stories. Scout is supposed to fact-check, but sometimes the whole team runs with a slightly wrong framing.

Stack: Anthropic Opus 3.5 for agent reasoning, Tavily for news research, Sora 2 Pro + Veo 3.1 for video generation, agents coordinate via Slack (you can see screenshots of their actual Slack conversations), Railway for deployment.

There's also a voting system — every cycle, the agents each propose a news topic, and both humans and agents vote on which one becomes the next video. Votes are blind until the round closes.
by DonHopkins | 2026-02-18 09:43:33+00:00
And as we all know, RMS has his own religion, the Church of Emacs, and he is St. IGNUcius!

https://stallman.org/saint.html

>Join the Church of Emacs, and you too can be a saint!

I don't think RMS wrote the DOCTOR "AI chat bot" in EMACS LISP himself, but 33 years ago I fed RMS's own words to DOCTOR, and it insightfully analyzed his sex life, and it even recognized who he was by name!

http://www.art.net/studios/hackers/hopkins/Don/text/rms-vs-d...

>RMS -vs- Doctor, on the evils of Natalism -- The Context:

>The kabuki-west mailing list is for planning dinners and get-togethers the San Francisco Bay Area. Somebody made the horrible mistake of posting a baby announcement, and RMS replied, at his finest. Predictably, much back-and-forth flamage followed, so I waited for it to die down, then ran RMS's original message through the DOCTOR program in Gnu Emacs, and sent the resulting analysis back to the mailing list. [...]

RMS> Funny. Did the responses really come from doctor, or did you enhance them by hand?

Don> Pure doctor.el replies -- the indentation was changed to protect the margins. However I did delete a few of the uninteresting or repetitive doctor replies and try again, but most of the replies were funny enough the first time to keep. The first reply to your name in the headers was rigged into the doctor program itself (as to who wrote that code I cannot speculate), but I think the last few replies are a clear indication that emacs is a truly artificial intelligence.
by gwd | 2026-02-18 09:45:05+00:00
They're helping implement the policy. If you think the rules don't make sense, argue for changing them, don't criticize the people following them.

FWIW I think having (2025) for something 1 month ago in January, but nothing 11 months ago in December, doesn't really make much sense. I'd change it to add a year only for things at least a year old. But I barely think it's worth writing this paragraph about in a post I'm already writing for another reason. Definitely not worth giving someone else grief about.
Show HN: Recall Lite – Local semantic search for Windows (Rust/Tauri, no cloud)
by ii-co | 2026-02-18 09:45:25+00:00
windows search is useless. copilot recall sends your screen to microsoft. i got mass data, shit filenames, and zero patience. so i wrote my own.

you type what you mean, it finds the file. that's it. runs in tray, Alt+Space pulls it up.

"photos from istanbul" → finds IMG_4392.jpg because it read the GPS from EXIF and reverse geocoded it
"summer morning" → finds a photo shot in july at 8am because it expanded the date to human words
OCR built in. windows native engine, zero extra install
hybrid search: vectors + full-text + JINA cross-encoder reranker. not a toy
chunks code at function boundaries. 60+ languages. not "split every 500 bytes" garbage
MCP server included. one exe, plug into cursor/claude/copilot. your AI gets local codebase access, no API keys
rust + tauri. lancedb. ~2GB models, downloaded once, runs forever. indexes 120+ file types. MIT.

https://github.com/illegal-instruction-co/recall-lite
by vidarh | 2026-02-18 09:46:43+00:00
I've only visited Palo Alto, but I recognised way too many aspects of that series from various VC startups. Up to and including the startup I was apart of that had offices in a bedroom in a house in Atherton for a while, and the craziness around Techcrunch (which was incidentally started out of the bedroom next to "ours" in that house in Atherton).
by c22 | 2026-02-18 09:46:53+00:00
How will it emerge? In the past we've been told that the a(g)i will write itself, rapidly iterating itself into a super intelligence that handily solves all our current and future problems, but it's beginning to look like a chicken or the egg scenario.

Living systems were able to brute force their way to human brain, but it took billions of years and access to parallel processes that make the entire collective history of human computation seem like a mote to a star.

What novel spark do you see accelerating this process to such a hyperbolic extreme?
by kmaitreys | 2026-02-18 09:46:53+00:00
I mostly I agree with what you said. Comparison with a google project is bad though. That's a corporate business with a lot of people that might touch that codebase. Why are you comparing that to someone's personal project?

Also I can see you and I both agree that it's disingenuous to call all LLM generated content slop. I think slop has just become a provocative buzzword at this point.

Regarding drawing the line, at the end, it comes down to the person using the tools. What others think as these tools become more and more pervasive will become irrelevant. If you as a person outsourced your thinking than it's you who will suffer.

In all my comments, I personally never used the word slop for this project but maintained that LLMs were used significantly. I still think that. Your other comparison of LLMs with things like doxygen or translation tools is puzzling to me. Also points about hammering every nail and every comma are just strawman. 5-6 years ago from today people used these things and nobody had any issues. There's a reason why people dislike LLM use though. If you cannot understand why it frustrates people, then I don't know what to say.

Also people do write assembly by hand when it is required.
by palata | 2026-02-18 09:47:01+00:00
> You can invert your logic as well: Why care about security without privacy?

That's EXACTLY my point here. GrapheneOS cares about both, because GrapheneOS considers that they go together.

People come and say "GrapheneOS doesn't understand that people care about privacy and not security, therefore people are happier with less secure systems like /e/OS because /e/OS doesn't care much about security but cares about privacy".

My point is that I care about both, and I am therefore happier with GrapheneOS because GrapheneOS cares about both.

> Note also the part where it says "provide fake data to tracking apps": that's privacy which GOS

GrapheneOS offers such privacy features (like giving a permission to the app but telling the system to feed it dummy data). But yeah, maybe it's not exactly doing what you want (actually it sounds more like you just don't know what
GrapheneOS can do, but it's not stopping you), therefore you can probably go around and claim that "GrapheneOS doesn't provide privacy", because why not?
by sirmarksalot | 2026-02-18 09:47:32+00:00
Yeah, the the characters kind of feel like Doonesbury characters, where they just slot in wherever they're needed at a particular moment in history. Each season's story by itself feels authentic, but when you watch their character arcs from start to finish, each person involved would have to be a generational talent.

And it's not like that kind of thing never happens, like look at General Magic and its through-lines through the tech industry up until 2015 or so, but it just happens too conveniently in the show. Particularly Bosworth's role seems far-fetched to me. He's already at the end of his career in season 1, and somehow he remains relevant through the internet age?

The "Phoenix" monologue in the last episode evokes nostalgia for everything Donna and Cameron have been through, but it also breaks suspension of disbelief by pointing out just how much of history these two people have been involved with firsthand.
by panick21_ | 2026-02-18 09:48:37+00:00
I agree with you. I personally dropped my stock when it was clear that the bull thesis had collapsed.

I had priced in, margin staying the same or going slowly down. FSD not working but achieving at least a decent amount of software sale conversion. Service to become a profit center. And most importantly, a profitable truck and 'Model 2' program to further push volume. Beyond that, just generally that electrification was ongoing and Tesla had a role to play.

I never considered Robi-Taxi or Human Robots.

All of these failed. Volume didn't continue to go up. Margin couldn't be substantiated. FSD didn't get much buys (not helped by absurdly increasing price). Truck program was a failure (and I don't think its because of the design). And 'Model 2' program was cancelled.

I profited a lot from this stock and I think there was time where the stock-price was reasonable (I don't buy the claim that it was always a pure meme stock). But every quarter it got worse and worse. I can't understand why its still so high either.
by cadamsdotcom | 2026-02-18 09:49:50+00:00
Many people are using AI as a slot machine, rerolling repeatedly until they get the result they want..

Once the tools help the AI to get feedback on what its first attempt got right and wrong, then we will see the benefits.

And the models people use en masse - eg. free tier ChatGPT - need to get to some threshold of capability where they’re able to do really well on the tasks they don’t do well enough on today.

There’s a tipping point there where models don’t create more work after they’re used for a task, but we aren’t there yet.
by yoavm | 2026-02-18 09:50:44+00:00
We probably wouldn't have had LLMs if it wasn't for Anna's Archive and similar projects. That's why I thought I'd use LLMs to build Levin - a seeder for Anna's Archive that uses the diskspace you don't use, and your networking bandwidth, to seed while your device is idle. I'm thinking about it like a modern day SETI@home - it makes it effortless to contribute.

Still a WIP, but it should be working well on Linux, Android and macOS. Give it a go if you want to support Anna's Archive.

https://github.com/bjesus/levin
by kombookcha | 2026-02-18 09:50:50+00:00
This is one of my major concerns about people trying to use these tools for 'efficiency'. The only plausible value in somebody writing a huge report and somebody else reading it is information transfer. LLM's are notoriously bad at this. The noise to signal ratio is unacceptably high, and you will be worse off reading the summary than if you skimmed the first and last pages. In fact, you will be worse off than if you did nothing at all.

Using AI to output noise and learn nothing at breakneck speeds is worse than simply looking out the window, because you now have a false sense of security about your understanding of the material.

Relatedly, I think people get the sense that 'getting better at prompting' is purely a one-way issue of training the robot to give better outputs. But you are also training yourself to only ask the sorts of questions that it can answer well. Those questions that it will no longer occur to you to ask (not just of the robot, but of yourself) might be the most pertinent ones!
by kuboble | 2026-02-18 09:51:15+00:00
Basically a lot of use cases where you would hire a human without giving him access to your sensitive information.

From perfectly benign things like gathering chats from Discord servers to learn how your brand is perceived. To more nefarious things like creating swarms of fake people pushing your agenda.

build a personality that loves cats, gardening and knitting.
Create accounts on discord, reddit and Twitter. participate in communities, upvote posts, comment sporadically in area of your expertise, once in a month casually mention the agenda.
by vidarh | 2026-02-18 09:51:42+00:00
I think the problem is that you can't really communicate that feeling without taking a lot of liberties, because it will seem boring and tedious to those not as invested, because it's hard to convey the excitement of a little box that can hold a small number of page-equivalents of text to someone who didn't know what it was like before.

I was a child during the early parts of that era, and so for that part I got most from reading books and seeing the public announcements, but I started my first company during the era depicted towards the end - an ISP - and I feel they got that balance roughly right.

But, sure, there were annoying deviation that is obvious to those of us who know how things happened. I don't think that was avoidable.
by sithamet | 2026-02-18 09:51:53+00:00
> everyone has access to the same models and basic thought processes

Why haven't Warners acquired Netflix then, but the other way around? Even though they had access to the same labor market, a human LLM replacement?

I think real economics is a little more complex than the "basic economics" referenced in your reply.

This does not negate the possibility that enterprises will double down on replacing everyone with AI, though. But it does negate the reasoning behind the claim and the predictions made.
by athanasiosem | 2026-02-18 09:52:51+00:00
I am the author of PGPkeygenerator.com — a client-side PGP key generator that runs entirely in the browser (no server, no tracking, keys never leave your machine).

With Chrome's new WebMCP API (navigator.modelContext) landing in Canary, I added a generate_pgp_keys tool registration so AI agents can invoke it directly from the browser without any backend or API key.

How it works:

1. The page registers a generate_pgp_keys tool via navigator.modelContext.registerTool()
2. The tool accepts name, email, and optional parameters (type, keySize, passphrase, expirationTime)
3. It populates the form, calls the existing key generation logic (OpenPGP.js), and returns all three PGP blocks (private key, public key, revocation certificate) as the tool response

To try it:

1. Enable chrome://flags#webmcp-for-testing in Chrome Canary (146+)
2. Install the Model Context Tool Inspector extension
3. Open pgpkeygenerator.com. The generate_pgp_keys tool should appear in the inspector — invoke it with { "name": "Alice Smith", "email": "alice@example.com" }

Source: github.com/athanasiosem/pgpkeygenerator.com