MurphyA/hacker-news huggingface dataset:
by apignotti | 2026-02-18 12:52:18+00:00
Hello HN community, I am very happy to share with you BrowserPod for Node.js - a sandboxed Node runtime, compiled to WebAssembly, that runs completely in the your browser.

BrowserPod builds on our previous work on WebAssembly virtualization, see WebVM (https://webvm.io) as an example. The environment is not a simple set of shims, but the "real" Node.js, including support for filesystem, multiple processes and outbound and inbound networking.

This latest feature is powered by "Portals", shareable public URLs that let any user you want, anywhere on the internet, access full-stack applications running locally in your browser. Portals can be used to power live demos of full-stack frameworks, previewing what you (or your agent) are building and sharing the state of your app with testers, colleagues or customers.

Node.js is just the first "engine" of BrowserPod. Behind the scenes there is a real WebAssembly kernel and we are soon going to support more languages, with Python, Ruby, Go and Rust coming first in our pipeline.

Later in the year we expect to merge back our previous work on x86 virtualization into BrowserPod, and be able to run arbitrary binary containers safely sandboxed in the browser.

Let us know what you think.
by marginalia_nu | 2026-02-18 12:53:13+00:00
There have been times in history when merely having the ability to turn an idea to software has been such a marketable skill you could fairly effortlessly get rich off it, like the early mobile app era saw some examples of that.

Those times were always pretty brief, and those markets were quickly saturated by people looking to make it rich. It was certainly not the state of anything in the years leading up to agentic coding.
by seba_dos1 | 2026-02-18 12:53:18+00:00
This means GOS is not AOSP either, because it's not that particular project. It takes the Android source produced by AOSP and builds on it. But what you agreed to is just pointless pedantry that leads directly to this outcome, as everyone uses "AOSP" to refer to what AOSP produces (which is a particular flavor of Android).

It stops being ironic when you take some time to understand that the two cases only appear related, but are actually quite different. You could even say opposite.
by fsloth | 2026-02-18 12:54:41+00:00
"reasonably stable company"

If the other company is "equally stable" then pricing offers leverage sure.

But there are lot of situations were _any_ license costs in some given range are so trivial nobody actually cares wether it's $15 / month or $1 / month.

There are B2B customers who are ready to pay license premium for known brand vendor, even if they would use just a subset of the available features. Change is always a risk, internal efforts are better spent than counting beans, etc.
by saikatd2018 | 2026-02-18 12:55:00+00:00
Hey everyone, I've been a PM for 5 years and always struggled with JIRA's slow roadmaps.

So I built TrackLens - a tool that pulls your Epics and lets you manage them locally with a real-time Gantt view.

Tech Stack: React 19, Tailwind, Node.js (Proxy).

It's free and open source. I'd love your feedback.
by ZeroGravitas | 2026-02-18 12:55:31+00:00
> The rational fear of those who dislike economic inequality is that the rich will convert their economic power into political power: that they’ll tilt elections, or pay bribes for pardons, or buy up the news media to promote their views.

> I used to be able to claim that tech billionaires didn’t actually do this—that they just wanted to refine their gadgets. But unfortunately in the current administration we’ve seen all three. -- Paul Graham
by lelanthran | 2026-02-18 12:55:39+00:00
> We could still be in the PC DOS 3.X era in this timeline. Wait until we hit the Windows 3.1, or 95 equivalent. Personally, I have seen shocking improvements in the past 3 months with the latest models.

While we're speculating, here's mine: we're in the Windows 7 phase of AI.

IOW, everything from this point on might be better tech, but is going to be worse in practice.
by cunibon | 2026-02-18 12:56:12+00:00
I built ReciPath because most recipe apps today have high monthly costs, overbearing social features, and require an internet connection just to see a shopping list.

THE APPROACH:
I’m primarily a Flutter developer. For this project, I wanted to experiment with a "database-driven UI" flow. Instead of heavy state management boilerplate, the UI state is tightly coupled to a local Drift (SQLite) DB. If it's in the DB, it's in the UI.

TECHNICAL HIGHLIGHTS:

- Offline First: Everything works locally. Accounts are optional and only used for syncing via Supabase.
- Shopping Planner: You select recipes, and the app generates a shopping list.
- Smart Timers: When you start a recipe, it tracks your actual cooking time to provide better averages later. It also handles per-step timers (e.g., a 60-minute oven timer) with local notifications and sounds.
- The Sharing Challenge: Since the app is self-contained, sharing recipes is currently done via JSON files. The hard part is mapping imported "grocery items" to local ones. The app tries to match by barcode and name, but I’d love to hear ideas on how to streamline this mapping process.

ROADMAP: BYOT AI INTEGRATION

- I'm currently looking into adding "Bring Your Own Token" AI support. The goal is to let users use their own API keys (OpenRouter/OpenAI/etc.) to import recipes directly from messy URLs or photos of physical cookbooks. Since recipe sites change their HTML constantly, using LLMs for schema mapping feels like the most robust way to keep the app lightweight without writing a thousand custom scrapers.

WHY OPEN SOURCE?
I was just tired of the bloat. I wanted a clean, open-source alternative that belongs to the user, not a subscription service.

I’d love feedback on the UX, the Drift-heavy architecture, or your thoughts on the recipe-sharing schema!

GitHub: https://github.com/Cunibon/recipath
Play Store: https://play.google.com/store/apps/details?id=com.cunibongam...
by EliasNowakGreen | 2026-02-18 12:56:42+00:00
Hi HN! I built TokCoach after talking to TikTok creators struggling with limited analytics.

Features:
- Track follower growth over time
- AI coach for content strategy (powered by Gemini)
- Video management and custom metrics
- Completely free

Built in 2.5 days using Flask + SQLite. Would love feedback from the community!
by datsci_est_2015 | 2026-02-18 12:56:54+00:00
I’m bearish on AI, but I still think this is disingenuous. My grade school math teachers were probably not well-versed in Calculus and Real Analysis, but they helped me learn my time tables just as well.

AI is great at exposing you to what you don’t even know you don’t know: your personal unknown unknowns, the complexity you’re completely unaware of.
by krapp | 2026-02-18 12:57:18+00:00
It isn't even just the aliens (although my headcanon is that the human belief that they "evolved beyond their base instincts" is part a trauma response to first contact and World War 3, and part Vulcan propaganda/psyop.) Star Trek's post scarcity society depends on replicators and transporters and free energy all of which defy the laws of physics in our universe (on top of FTL.)

We'll never have Star Trek. We'll also never have SkyNet, because SkyNet was too rational. It seems obvious that any AGI that emerges from LLMs - assuming that's possible - will not behave according to the old "cold and logical machine" template of AI common in sci-fi media. Whatever the future holds will be more stupid and ridiculous than we can imagine, because the present already is.
by jmbwell | 2026-02-18 12:57:46+00:00
Color schemes voluntarily added by the user to an app like vim, great.

All the more reason for developers to keep the app itself responsive to the user’s environment by default.

Don’t bake in elaborate visual choices. It’s a usability thing first and a style thing somewhere much farther down the list.

Keep it simple from the factory. Don’t get in the way of customization. Let the user’s environment do the work of adapting it to the user.
by lelanthran | 2026-02-18 12:57:58+00:00
> I would like to see the day when the context size is in gigabytes or tens of billions of tokens, not RAG or whatever, actual context.

Might not make a difference. I believe we are already at the point of negative returns - doubling context from 800k tokens to 1600k tokens loses a larger percentage of context than halving it from 800k tokens to 400k tokens.
by imiric | 2026-02-18 12:58:34+00:00
But this is not a trick question[1]. It's a straightforward question which any sane human would answer correctly.

It may trigger a particularly ambiguous path in the model's token weights, or whatever the technical explanation for this behavior is, which can certainly be addressed in future versions, but what it does is expose the fact that there's no real intelligence here. For all its "thinking" and "reasoning", the tool is incapable of arriving at the logically correct answer, unless it was specifically trained for that scenario, or happens to arrive at it by chance. This is not how intelligence works in living beings. Humans don't need to be trained at specific cognitive tasks in order to perform well at them, and our performance is not random.

But I'm sure this is "moving the goalposts", right?

[1]: https://news.ycombinator.com/item?id=47060374
by wongarsu | 2026-02-18 13:00:30+00:00
The benefit of a laser is that it can not only remove material, it can also discolor it. Either as a side effect of removing it or simply as a lower-power setting. And discolorations can be picked up with optical methods, which are far more accessible, reliable and higher density than 3d scanning.

Another variation of this is how we encode information into granite and other stones in Western funeral rites (grave stones): you engrave the information, then fill the groove with pigment. The pigment is susceptible to weathering, but the 3d information is pretty resistant. When the pigment is too worn down you just smear some more on there and wipe the excess away, leaving pigment only in the grooves, making the message clearly visible again
by postpire | 2026-02-18 13:01:06+00:00
Hey HN,

I built Postpire because I was frustrated with how much manual fixing AI-generated SEO articles required before publishing.

I run a few small projects, and while AI tools could generate drafts quickly, the output often had structural issues, generic phrasing, or factual inconsistencies. I still had to spend significant time editing before I felt comfortable publishing anything.

Postpire was built to solve that workflow problem.

The process is simple:
• AI generates the initial draft based on the target keyword
• A human review step improves structure, clarity, and correctness
• The goal is to produce something much closer to publish-ready

I’m not trying to fully automate content creation — the goal is to reduce the time from idea to publishable article while keeping quality under control.

Right now it’s being used mainly by founders and small teams doing their own SEO.

I’d really appreciate any feedback, criticism, or questions. I’m especially interested in hearing how others here are handling SEO content workflows.
by mapontosevenths | 2026-02-18 13:01:09+00:00
> he's this amazing engineer, who could, possibly, "solve" FSD overnight

Even if thay were true many people hate Elon now. Enough that they will pass on any technology he is the only purveyor of.

After he celebrated letting children starve (USAID) by dancing on stage with a chainsaw many people decided to never buy any Musk product for any reason.

Worse, many people who dont care about politics at all won't get involved, because Musk is an unstable drug user and its not wise to entangle yourself in his business affairs.
by NekkoDroid | 2026-02-18 13:02:41+00:00
> but do you really expect a review process to identify that a diagram is a copy from another one some rando already published on the internet years ago?

We aren't talking about just some random image from some random blog. The article we are talking about is about a specific topic, which when searched online one of the first is the article containing the original image (at least for google, bing seems to be really struggling to give me the article but under images it is again the first).

I would cut some slack if this were a really obscure topic almost noone talks about, but it's been a thing talked about in the programmer space for ages.
by ksec | 2026-02-18 13:04:17+00:00
This is what I have been saying for sometime. Working inside different Goverment department you see this happening every day. Email and report bouncing back and forth with no actual added value while feeling extremely productive. That is why private sector and public sector generally don't mix well. It is also one reason why I said in some of my previous post LLM could replace up to 70% of Goverment's job.

Edit: If anyone haven't watched Yes Minster, you should go and watch it, it is a documentary on UK Government that is still true today as it was 40-50 years ago.
Show HN: A tool to help you remember shit you are interested in
by jpatl | 2026-02-18 13:04:21+00:00
A few months ago I opened my notes app to find something important. I couldn’t find it. Instead, I found dozens of half-finished thoughts, article highlights, screenshots from YouTube, research notes, business ideas I had at 2am, university notes, and “important concepts” I had promised myself I’d revisit. The worst part wasn’t that it was messy. The worst part was that I remembered writing all of it — I just didn’t remember what it actually said.

That’s when it hit me: we don’t have an information problem anymore. We have a retention problem. We save everything. Articles. PDFs. Tweets. Meeting notes. Video insights. Random ideas. But two weeks later, most of it is gone from our head. The insight decays. The context disappears. The connection between ideas fades. Our notes slowly turn into an archive instead of an asset.
What frustrated me most was realizing I kept relearning the same things. I’d read about mental models, startup distribution, learning science, systems thinking — and every time it felt new. But it wasn’t new. I’d seen it before. I just didn’t retain it. That’s when I had an uncomfortable realization: my “second brain” wasn’t a brain at all. It was a storage locker. It stored information, but it didn’t help me remember or use it.

Most tools are optimized for storing, organizing, tagging, formatting, linking. They assume you’ll come back and reread your notes. But you usually don’t. And even if you do, rereading isn’t the same as remembering. Real retention requires re-exposure, active recall, and spaced repetition — the same principles behind learning science — but applied to everyday thinking and work, not flashcards and exam prep.

So I started asking a different question. Instead of “How do I organize my notes better?” I asked, “How do I make sure I actually remember what I capture?” That shift changed everything. What if your notes didn’t just sit there? What if they occasionally asked you to explain an idea in your own words? What if they reminded you of a concept right before you forgot it? What if they connected new thoughts to old ones automatically and resurfaced insights you saw months ago when they became relevant again?
That’s the idea I started building around. I’m working on something called Neuron. The core loop is simple: Capture → Understand → Remember → Retrieve → Reuse. You throw everything in — notes, links, PDFs, highlights, voice ideas — and the system handles structure automatically. Behind the scenes it extracts key ideas, builds a living knowledge graph, generates contextual recall prompts, and schedules spaced repetition quietly in the background. You don’t “study.” You just spend a few minutes a day reinforcing what actually matters.

The goal isn’t to build another note-taking app. It’s to build something memory-first. Something that turns knowledge into something that compounds instead of decays. If this resonates - especially if you feel like you consume way more than you retain — I’d genuinely love your thoughts and criticism.

You can check it out here: https://neuronapp.tech
by miladyincontrol | 2026-02-18 13:04:41+00:00
The idea of arch was never that its "supposed to be hard mode", its meant to hit what many of it's users consider the sweet spot of not being too opinionated but not leaving every single factor up to the user either. For many people that balance makes it in fact easymodo.

Calling it hard mode is putting it on a pedestal, a weird one that ignores much less opinionated linux distros and setups like Gentoo.
Show HN: SciCraft – generate scientific Claude Code skills on demand (176 built)
by jaechang | 2026-02-18 13:05:04+00:00
Most Claude Code plugins ship a fixed set of skills and stop there. For
general software development, that's fine. For scientific research, it's
a fundamental mismatch.

Every scientist works at a different intersection of tools. A computational
biologist running GWAS uses a completely different stack than a structural
biologist doing MD simulations, or a medicinal chemist running virtual
screens, or a microscopist doing image segmentation. No static plugin can
anticipate that breadth — and the moment your workflow touches a tool
that isn't covered, the plugin becomes useless for that task.

SciCraft is built around a CLAUDE.md that encodes a complete skill authoring
workflow. Give Claude Code any scientific tool name:

"Add a skill for CellRanger"
"Add a skill for CREST structural variant caller"
"Add a skill for our internal mass spec preprocessing pipeline"

It runs a 6-step process:

Topic → Classify (pipeline / toolkit / database / guide)
→ Category (pick from 11 life sciences domains)
→ Research (official docs, GitHub, PyPI)
→ Author (SKILL.md: 10+ runnable code blocks, Key Parameters
table, Troubleshooting matrix)
→ Register (registry.yaml entry)
→ Validate (pytest suite checks structure and code depth )

The result is a CI-validated skill file committed to your repo — not a
one-off answer, but a permanent reusable asset available in every future
session. Your collaborators inherit it too.

Scientific computing makes this especially valuable:
- Life sciences libraries (Scanpy, RDKit, MDAnalysis, BioPython) have
complex, non-obvious APIs that LLMs frequently hallucinate
- The field moves fast — tools released last month have no training data
- Lab-specific pipelines and instruments will never appear in any
off-the-shelf plugin
- Research scope shifts constantly: a lab pivoting from bulk RNA-seq to
spatial transcriptomics needs a completely different skill set overnight

The pytest suite enforces minimum code block counts, required section
structure, parameter table depth, and troubleshooting rows — so generated
skills are immediately usable, not rough drafts.

---

The repo ships 176 pre-built scientific skills across genomics, drug
discovery, proteomics, cell biology, and biostatistics (Scanpy, GATK,
RDKit, DESeq2, AutoDock Vina, cBioPortal, gnomAD, and more) so common
workflows are covered from day one. But the 176 are a starting point —
the authoring system is what makes SciCraft adapt to your specific research,
not just the research someone else anticipated.

The design uses progressive disclosure: only each skill's description is
in context during planning. The full file loads on demand. Context stays
lean; precise scientific API knowledge is available when the agent needs it.

Curious whether others have hit the ceiling of static plugin systems in
research contexts — and what approaches you've tried for keeping domain
knowledge current with a fast-moving field.

https://github.com/jaechang-hits/scicraft
by seanhunter | 2026-02-18 13:05:12+00:00
> I just want to know why people do stupid things like this. Does he think that he's providing something of value?

This is a good question. If you go to your settings on your hn account and set “showdead” to “yes” you’ll see that there are dozens of people who are making bots who post inane garbage to HN comment threads for some reason. The vast majority end up being detected and killed off, but since the moltbook thing kicked off it’s really gone into hyperdrive.

It definitely strains my faith in humanity to see how many people are happy to say “here’s something cool. I wonder what it would be like if I ruined it a bit.”
by micik | 2026-02-18 13:05:19+00:00
> 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.

i may put this into my email signature with your permission, this is a whip-smart sentence.

and it is true. i used AI to "curate information" for me when i was heads-down deep in learning mode, about sound and music.

there was enough all-important info being omitted, i soon realized i was developing a textbook case of superficial, incomplete knowledge.

i stopped using AI and did it all over again through books and learning by doing. in retrospect, i'm glad to have had that experience because it taught me something about knowledge and learning.

mostly that something boils down to RTFM. a good manual or technical book written by an expert doesn't have a lot of fluff. what exactly are you expecting the AI to do? zip the rar file? it will do something, it might look great, lossless compression it will be not.

P.S. not a prompt skill issue. i was up to date on cutting edge prompting techniques and using multiple frontier models. i was developing an app using local models and audio analysis AI-powered libraries. in other words i was up to my neck immersed in AI.

after i grokked as much as i could, given my limited math knowledge, of the underlying tech from reading the theory, i realized the skill issue invectives don't hold water. if things break exactly in the way they're expected to break as per their design, it's a little too much on the nose. even appealing to your impostor syndrome won't work.

P.P.S. it's interesting how a lot of the slogans of the AI party are weaponizing trauma triggers or appealing to character weaknesses.

"hop on the train, commit fully, or you'll be left behind" > fear of abandonment trigger

"pah, skill issue. my prompts on the other hand...i'm afraid i can't share them as this IP is making me millions of passive income as we speak (i know you won't probe further cause asking a person about their finances is impolite)" > imposter syndrome inducer par excellence, also FOMO -- thinking to yourself "how long can the gold rush last? this person is raking it in!! what am i doing? the miserable sod i am"

1. outlandish claims (Claude writes ALL the code) noone can seem to reproduce, and indeed everyone non-affiliated is having a very different experience

2. some of the darkest patterns you've seen in marketing are the key tenets of the gospel

3. it's probably a duck.

i've been 100% clear on the grift since October '25. Steve Eisman of the "Big Short" was just hopping onto the hype train back then. i thought...oh. how much analysis does this guru of analysts really make? now Steve sings of AI panic and blood in the streets.

these things really make you think, about what an economy even is. it sure doesn't seem to have a lot to do with supply and demand, products and services, and all those archaisms.
by kristopolous | 2026-02-18 13:05:20+00:00
My streaming markdown renderer does something like that https://github.com/day50-dev/Streamdown

You define a baseline color in HSV and then everything else is a multiplier of that

For example

[style]

HSV = [0.7, 0.5, 0.5]

Dark = { H = 1.0, S = 1.2, V = 0.25 } # Make dark elements less saturated and darker

Symbol = { H = 1.0, S = 1.8, V = 1.8 } # Make symbols more vibrant

As a result you can simply move around the HSV to your preference in the config and things don't look like garbage where you have to hand tweak every color to get something legible.

For example, this simple loop https://github.com/day50-dev/Streamdown?tab=readme-ov-file#c...

It's effectively a swatch