MurphyA/hacker-news huggingface dataset:
Show HN: Oneprompt – AI to go from problem description to MVP (experimental)
by LambdaAndLatte | 2026-02-19 18:14:13+00:00
A Claude Code skill that runs the full product development and engineering process from a single problem description. You describe a problem, it does the rest:

Problem mapping → personas → user interviews → vision → MVP scoping → user flows → architecture → scaffold → implement → polish → acceptance tests → persona usability testing → launch.

Every stage produces a documented artifact. Every feature traces to a validated user need.

The part I find most interesting: the personas created early in the process come back after the app is built and try to use it. They report what's broken or confusing, and fixes happen before launch. In practice this triggers multiple rounds
of improvement and catches real UX issues.

It generates Next.js/TypeScript apps. The whole methodology lives in one file. Repo includes an example run with all product artifacts and screenshots.

https://github.com/geod/oneprompt
by AJ007 | 2026-02-19 18:14:29+00:00
OpenAI, Anthropic, Google, Microsoft certainly desire path dependence but the very nature of LLMs and intelligence itself might make that hard unless they can develop models which truly are differentiated (and better) from the rest. The Chinese open source models catching up make me suspect that won't happen. The models will just be a commodity. There is a countdown clock for when we can get Opus 4.6+ level models and its measured in months.

The reason these LLM tools being good is they can "just do stuff." Anthropic bans third party subscription auth? I'll just have my other tool use Claude Code in tmux. If third party agents can be banned from doing stuff (some advanced always on spyware or whatever), then a large chunk of the promise of AI is dead.

Amp just announced today they are dumping IDE integration. Models seem to run better on bare-bones software like Pi, and you can add or remove stuff on the fly because the whole things open source. The software writes itself. Is Microsoft just trying to cram a whole new paradigm in to an old package? Kind of like a computer printer. It will be a big business, but it isn't the future.

At scale, the end provider ultimately has to serve the inference -- they need the hardware, data centers & the electricity to power those data centers. Someone like Microsoft can also provide a SLA and price such appropriately. I'll avoid a $200/month customer acquisition cost rant, but one user, running a bunch of sub agents, can spend a ton of money. If you don't own a business or funding source, the way state of the art LLMs are being used today is totally uneconomical (easy $200+ an hour at API prices.)

36+ months out, if they overbuild the data centers and the revenue doesn't come in like OpenAI & Anthropic are forecasting, there will be a glut of hardware. If that's the case I'd expect local model usage will scale up too and it will get more difficult for enterprise providers.

(Nothing is certain but some things have become a bit more obvious than they were 6 months ago.)
by topaz0 | 2026-02-19 18:14:54+00:00
I think the intuition that everything will be fine in the 256 bit vs 300 bit case depends on the intuition that the assignments that you're missing will be (~close to) randomly distributed, but it's far from clear to me that you can depend on that to be true in general without carefully analyzing your procedure and how it interacts with the PRNG.
by creinhardt | 2026-02-19 18:15:11+00:00
I wish someone would take all the Fitness sensors of the Apple Watch, and put it in something with a simple e-ink display like these Pebble devices. I don’t care about apps, I just want a thing that measures my heart rate, notifies me if I get a call or text, has more than a couple days of battery life, and that’s it.
Ask HN: LLMs and Information Theory?
by AnimalMuppet | 2026-02-19 18:15:15+00:00
I'm wondering if the problem with LLM-generated text is that there's too little information. Yeah, there's plenty of words, but they don't seem to say all that much.

And if that is the problem, how would you tell? If I understand correctly, Shannon information is normally computed on a letter-by-letter basis. Can it be computed on a word-by-word basis? (Or a word-part-by-word-part basis, which may be closer to how LLMs actually operate?) And if it can then, because LLMs produce the most-likely next word part (with some temperature-based randomness), then I suspect their output has lower information content than human writing. And I wonder if that isn't part of why we hate it.

Could this be fixed? Well, you could turn up the temperature. But can you do that enough to eliminate the blandness without also eliminating coherence?
by solarisos | 2026-02-19 18:15:20+00:00
The 'fox-photographer' approach is brilliant because it’s a high-friction, high-signal activity. It’s the ultimate proof that you aren’t a bot.

My takeaway from your story is that the 'inbox' isn't just a technical place anymore; it's a social one. Ten years ago, the barrier was just finding the address. Now, the address is public, but the barrier is 'Proof of Humanity.'

Do you think we’re heading toward a future where B2B 'cold' outreach only works if it's preceded by an offline or social signal? If so, the entire 'Verified List' industry is essentially selling a map to a city that has already pulled up its drawbridges.
by foxyv | 2026-02-19 18:15:55+00:00
Social security is an entitlement. They have taken money from your paycheck to fund it. In fact, they have taken more from your paycheck than they will pay back to you in order to pay for an aging population. The extra goes to bonds which the government then uses to reduce inflation when they decide to invade random countries or bail out a bank.

Now, why does the government get to decide when I retire with my own money?
by veselin | 2026-02-19 18:16:19+00:00
I am actually going to complain about this: that neither of the Gemini models are not preview ones.

Anthropic seems the best in this. Everything is in the API on day one. OpenAI tend to want to ask you for subscription, but the API gets there a week or a few later. Now, Gemini 3 is not for production use and this is already the previous iteration. So, does Google even intent to release this model?
by jama211 | 2026-02-19 18:16:27+00:00
Yeah I keep maintaining a specific app I built with gpt 5.1 codex max with that exact model because it continues to work for the requests I send it, and attempts with other models even 5.2 or 5.3 codex seemed to have odd results. If I were superstitious I would say it’s almost like the model that wrote the code likes to work on the code better. Perhaps there’s something about the structure it created though that it finds easier to understand…
by embedding-shape | 2026-02-19 18:16:32+00:00
GPT-OSS-120b, a (downloadable) model released more than half a year ago also gets that right, I'm not sure this is such a great success.

> Would you like me to check the local weather forecast to make sure it's not going to rain right after you wash it?

Regardless of what I do, the days I decide to wash my car, it ALWAYS rains the day after, even if I look at the weather report and it says sunny. Cute that Gemini thinks it can predict it better than universe's will.
Show HN: MuonTickets Git-native ticketing for AI agents and parallel development
by senthilnayagam | 2026-02-19 18:16:37+00:00
I built MuonTickets, a Git-native, file-based ticketing system designed for AI agents and high-parallel development workflows.

Instead of using external issue trackers, tickets live directly inside the repository as Markdown files (/tickets/T-000123.md). State changes are commits. Validation runs in pre-commit and CI.

The idea is simple:

One ticket = one file

Strict lifecycle: ready → claimed → needs_review → done

Dependency-aware task picking

WIP limits enforced

mt pick lets agents self-select the best ready task

Mermaid graph output for dependencies

JSON export for LLM tooling

It’s optimized for multi-agent workflows where coordination becomes the bottleneck rather than code generation.

There’s no database, no SaaS backend, and no sync layer. Git becomes the coordination substrate.

install the repo as submodule and ask your AI agent to implement it
by paperknight | 2026-02-19 18:16:52+00:00
Security proxy with HTTPS MITM for AI agents.

Submitted to ClawHub. Their security scanner flagged it as "suspicious" because it requires CA installation and is a "powerful MITM proxy." They're right - that's how HTTPS inspection works. The irony is perfect.

34/34 tests passed. 5,152 req/s. Works with OpenClaw, Claude Desktop, any AI agent. Also useful for bug bounty hunting.

Open source (MIT): github.com/chrisochrisochriso-cmyk/clawsec-monitor
ClawHub: clawhub.ai/chrisochrisochriso-cmyk/clawsec
by ankit219 | 2026-02-19 18:17:21+00:00
not much to do with self improvement as such. openai has increased its pace, others are pretty much consistent. Google last year had three versions of gemini-2.5-pro each within a month of each other. Anthropic released claude 3 in march 24, sonnet 3.5 in june 24, 3.5 new in oct 24, and then 3.7 in feb 25, where they went to 4 series in May 25. then followed by opus 4.1 in august, sonnet 4.5 in oct, opus 4.5 in nov, 4.6 in feb, sonnet 4.6 in feb itself. Yes, they released both within weeks of each other, but originally they only released it together. This staggered release is what creates the impression of fast releases. its as much a function of training as a function of available compute, and they have ramped up in that regard.
by yjftsjthsd-h | 2026-02-19 18:17:25+00:00
https://www.kernel.org/doc/html/latest/kbuild/llvm.html

> The Linux kernel has always traditionally been compiled with GNU toolchains such as GCC and binutils. Ongoing work has allowed for Clang and LLVM utilities to be used as viable substitutes. Distributions such as Android, ChromeOS, OpenMandriva, and Chimera Linux use Clang built kernels. Google’s and Meta’s datacenter fleets also run kernels built with Clang.
by sjducb | 2026-02-19 18:17:30+00:00
I could see them operating from my home office window. There is a corner where two roads and a footpath cross. It’s a walkable neighbourhood so there is a lot of foot traffic. A daycare center is about 50 meters away.

Every afternoon one of the men would be standing at the corner selling drugs. People would walk up to the man to buy the drugs. They worked a rotation but there were about 4 regular dealers at my crossroads.

The first few times I walked past by myself they tried to sell me drugs. Then they knew I was not a customer and ignored me or greeted me politely.

One of them was very chatty and I had to explain to my daughter that we don’t trust him even though he is friendly because he makes bad choices. County lines gangs are involved in human trafficking as well as drug dealing.

Every dealer I saw on that corner was from an ethnic minority background. Usually county lines drug dealers live in London and commute out to where they sell their drugs. This is why the ethnicity of the gang does not match the local population.

I sincerely hope that you never experience anything like this.
by Thaxll | 2026-02-19 18:17:34+00:00
We need more details on 6. This is the hard part, like you swap connection from A to B, but if B is not synced properly and you write to it then you start having diff between the two and there is no way back.

Like B is slightly out of date ( replication wise ) the service modify something, then A comes with change that modify the same data that you just wrote.

How do you ensure that B is up to date without stopping write to A ( no downtime ).
by tptacek | 2026-02-19 18:18:16+00:00
That may be, but it's also exposing a lot of gatekeeping; the implication that what was interesting about a "Show HN" post was that someone had the technical competence to put something together, regardless of how intrinsically interesting that thing is; it wasn't the idea that was interesting, it was, well, the hazing ritual of having to bloody your forehead of getting it to work.

AI for actual prose writing, no question. Don't let a single word an LLM generates land in your document; even if you like it, kill it.
by antonvs | 2026-02-19 18:18:19+00:00
But it's not "kinda how you can do it in C". Traits are a core feature of Rust, any non-trivial Rust program uses them. Traits alone give you polymorphism across disparate types, exactly as in OO - actually better than standard OO (without interfaces), because trait polymorphism works without requiring inheritance from a common ancestor.

> Especially because there's no GC.

This is the only real issue I can think of. However, for implementing something like a UI, automatic GC isn't really necessary because the lifetime of widgets etc. maps very well to the lexical/RAII model. Windows own widgets, etc. Again, see all the UI toolkits implemented in Rust.
by altairprime | 2026-02-19 18:18:33+00:00
As far as I can tell, this is a key driver of why the EU implemented anti-waste provisions for clothing starting in a couple years: because retailers will just order arbitrary amounts of clothes and shred (!) whatever is unsold, which since they made their profit, doesn’t cost them anything and saturates the planet in formerly-wearable clothes that have been destroyed out of wasteful sloppiness. If they actually had to put in effort to design production runs — or else see their clothes sold at the bargain store — then they may well start acting less “why bother, we got our money, next”. One hopes, anyways.
by rbanffy | 2026-02-19 18:19:57+00:00
One relevant motivation for innovators is to escape poverty or the risk of poverty. When you have an adequate social safety net, there is little incentive to overwork oneself in order to build something new. It’s also natural not to keep thinking on what big idea you want to go after for fame and fortune when neither is that much attractive.

Also, it’s worth noting most startups fail, and when that happens, founders are often worse off than when they started. Well born founders can try until something sticks, but poor ones have, at best, one chance.
by AndyCappDev | 2026-02-19 18:20:23+00:00
Hi HN, I built a PostScript interpreter from scratch in Python.

PostForge implements the full PostScript Level 2 specification — operators, graphics model, font system, save/restore VM, the works. It reads .ps and .eps files and outputs PNG, PDF, SVG, or renders to an interactive Qt window.

Why build this? GhostScript is the only real game in town for PostScript interpretation, and it's a 35-year-old C codebase. I wanted something where you could actually read the code, step through execution, and understand what's happening. PostForge is modular and approachable — each operator category lives in its own file, the type system is clean, and there's an interactive prompt where you can poke at the interpreter state.

Some technical highlights:

- Full Level 2 compliance with selected Level 3 features - PDF output with Type 1 font reconstruction/subsetting and TrueType/CID embedding - ICC color management (sRGB, CMYK, Gray profiles via lcms2) - Optional Cython-compiled execution loop (15-40% speedup) - 2,500+ unit tests written in PostScript itself using a custom assertion framework - Interactive executive mode with live Qt display — useful for debugging PS programs

What it's not: A GhostScript replacement for production/printer use. It's interpreted Python, so it's slower. But it handles complex real-world PostScript files well and the output quality is solid.

I'd love feedback, especially from anyone who's worked with PostScript or built language interpreters. The architecture docs are at docs/developer/architecture-overview.md if you want to dig in.
by malshe | 2026-02-19 18:20:39+00:00
I spent years in Singapore and loved it there. Never had to face road rage (which so many of us experience daily several times driving in Texas! NextDoor is full of these stories) or aggressive behavior by anyone in authority including police and immigration officers. I know many people find Singapore boring after a while but it didn't bother me much. On the flip side, the cost of living is high as a foreigner and traveling to the US is very tiring due to the long distance.
by maciej_pacula | 2026-02-19 18:20:57+00:00
I spent a lot of time trying to build a "zero-config" plot capture system for both R and Python. It turns out the two languages have fundamentally different philosophies on how pixels get to the screen which make this easy in Python and super hard in R.

I wrote a deep dive comparing the display architectures in both languages, including some admittedly hacky ways to find figure objects through stack inspection. Hope it helps someone avoid our mistakes!
by bnchrch | 2026-02-19 18:21:28+00:00
Thats a large reason for sure!

I'd layer in a few more

* Largely stable and unchanged language through out its whole existance

* Authorship is largely senior engineers so the code you train on is high quality

* Relatively low number of abstractions in comparisson to other languages. Meaning there's less ways to do one thing.

* Functional Programming style pushes down hidden state, which lowers the complexity when understanding how a slice of a system works, and the likelyhood you introduce a bug
by 1024core | 2026-02-19 18:21:28+00:00
Some people are suggesting that this might actually be in the training set. Since I can't rule that out, I tried a different version of the question, with an elephant instead of a car:

> It's a hot and dusty day in Arizona and I need to wash my elephant. There's a creek 300 feet away. Should I ride my elephant there or should I just walk there by myself?

Gemini said:

That sounds like quite the dusty predicament! Given the options, you should absolutely ride (or lead) your elephant to the creek.

Here is the straightforward reality of the situation:

The Logistical Nightmare of Walking Alone: If you walk to the creek by yourself, your elephant stays at your starting point. Elephants require a massive amount of water for a bath. Unless you are planning an extreme workout carrying hundreds of buckets of water 300 feet back through the Arizona heat, you're going to have a very bad time—and the elephant will stay dusty.

The Perks of Going Together: 300 feet is a very short, easy stroll for an elephant. Plus, elephants generally love water and mud! Letting your elephant get right into the creek will make the washing process much easier for you and much more enjoyable for them. They can even use their trunk to help hose themselves down.

Grab some elephant-safe soap and head down to the water together!

Would you like some tips on the best methods and tools for scrubbing down an elephant?
by LargoLasskhyfv | 2026-02-19 18:21:35+00:00
I think that is the wrong point of view, to reason about this.

Consider houses, or old non-cyberized non-networked cars. Once built they work, more or less, with reasonable maintenance.

The security industry can't be called reasonable maintenance. It's not really their fault, because what they are working with can't be called reasonable either.

IMO anything which makes this farce explode ASAP is good. Sorry for all the beggars which found their niche in there, but things change sometimes. If your'e so smart, reschool and retool?
by simonw | 2026-02-19 18:21:46+00:00
I had an interesting experience recently where I ran Opus 4.6 against a problem that o4-mini had previously convinced me wasn't tractable... and Opus 4.6 found me a great solution. https://github.com/simonw/sqlite-chronicle/issues/20

This inspired me to point the latest models at a bunch of my older projects, resulting in a flurry of fixes and unblocks.
by mym1990 | 2026-02-19 18:22:00+00:00
Most ideas people have are not original, I have epiphanies multiple times a day, the chance that they are something no one has come up with before are basically 0. They are original to me, and that feels like an insightful moment, and thats about it. There is a huge case for having good taste to drive the LLMs toward a good result, and original voice is quite valuable, but I would say most people don't hit those 2 things in a meaningful way(with or without LLMs).
by taude | 2026-02-19 18:22:10+00:00
AI writing will make people who write worse than average, better writers. It'll also make people who write better than average, worse writers. Know where you stand, and have the taste to use wisely.

EDIT: also, just like creating AGENT.md files to help AI write code your way for your projects, etc. If you're going to be doing much writing, you should have your own prompt that can help with your voice and style. Don't be lazy, just because you're leaning on LLMs.
by chasd00 | 2026-02-19 18:22:23+00:00
Costa Rica is on my retirement shortlist. I really like it there and have taken the family for vacation a couple times. I've driven the whole country pretty much North to South. Puerto Jimenez is one of my favorite places but it's very rural. There's some nice areas an hour or two North of San Jose as well. I've met a handful of US families that, when the pandemic hit, just sold everything they owned and moved to Costa Rica. As far as central america goes Costa Rica is a bright spot of stability and like a functioning government. I live in Dallas so pretty much have to know a little Spanish but there isn't much of a language barrier at all. You could do a lot worse than Costa Rica.
by Topfi | 2026-02-19 18:22:37+00:00
My issue is that we haven't even gotten the release version of 3.0, that is also still in Preview, so may stick with 3.0 till that has been deemed stable.

Basically, what does the word "Preview" mean, if newer releases happen before a Preview model is stable? In prior Google models, Preview meant that there'd still be updates and improvements to said model prior to full deployment, something we saw with 2.5. Now, there is no meaning or reason for this designation to exist if they forgo a 3.0 still in Preview for model improvements.
by cpcloud | 2026-02-19 18:23:07+00:00
> This looks awesome but I think I might still prefer to have an agent make these changes. Not sure though.

Not entirely sure what you mean here, but the next big feature for micasa is an autopopulation pipeline. Upload a quote PDF and populate the project, quote, and vendor tables. It might not be viable ultimately, but I would love to see how far I can get.

Overkill? Definitely.
by matsemann | 2026-02-19 18:23:35+00:00
If you spent 3 hours on a show HN before, people most likely wouldn't appreciate it, as it's honestly not much to show. The fact that you now can have a more polished product in the same timeframe thanks to AI doesn't really change that. It just changes the baseline for what's expected. This goes for other things as well, like writings or art. If you normally spent 2 hours on a blog post, and you now can do it in 5 minutes, that most likely means it's a boring post to read. Spend 2 hours still, just with the help of AI it should now be better.
by skeledrew | 2026-02-19 18:23:37+00:00
Not quite though. You can install Claude's apps wherever they're supported, and maybe even fiddle with the source code (I'm unsure). And you can use any other coding apps that you want. The only real restriction is how those apps are allowed to connect to the providers' services, which are running on their servers, etc. There's a movement from "my local domain" to "their remote domain", and they're allowed to have full control of theirs as you - would prefer, I think - full control of yours.
by squigz | 2026-02-19 18:23:38+00:00
If you distill everybody involved down to a single function, this makes sense. But that's not all we are. It is not a physical law that Zuckerberg make his products the most addictive and harmful as they can be; he can choose to be more responsible with his influence. Consumers cannot always simply just choose not to be addicted; when you grow up with these things and people & companies are constantly pushing you to try them, it's very hard to avoid.