MurphyA/hacker-news huggingface dataset:
Ask HN: Use-Cases for an Operating System with a Custom Kernel
by ayush_xeneva | 2026-03-07 17:31:37+00:00
If you were to be given an Operating System with a Custom Kernel, what features would you want it to have and what problems would you want it to solve?

We're currently building an OS by designing the Kernel strictly for XR, but we're interested to know what the community has to say.
by Kerrick | 2026-03-07 17:31:42+00:00
> It gets 50% more pull requests, 50% more documentation, 50% more design proposals

Perhaps this will finally force the pendulum to swing back towards continuous integration (the practice now aliased trunk-based development to disambiguate it from the build server). If we're really lucky, it may even swing the pendulum back to favoring working software over comprehensive documentation, but maybe that's hoping too much. :-)
by zameermfm | 2026-03-07 17:31:43+00:00
As we build software with AI agents—through tools like Cursor, VS Code, or Antigravity—Markdown files (often called specs in software development) are rapidly becoming part of the AI infrastructure layer. They act as a communication interface between humans, teams, and AI systems.

I’ve primarily used specs for two purposes.

First, for developing new features or fixing bugs. A spec becomes a development artifact where teams discuss design, trade-offs, costs, security implications, and architecture. AI agents are particularly good at exploring these aspects in depth. The entire discussion can live in one document or multiple linked documents, and when things change, agents can update the specs.

Second, for targeted analysis extracted from codebases. Sometimes you need to generate understanding for a specific audience or tool—compliance reviews, architecture analysis, cost simulations, or risk modeling. For example, I’ve built cost-simulation tools using YAML infrastructure specs derived from the codebase. The advantage is that the target audience does not need access to the entire repository—only the relevant spec.

In essence:

Specs give AI agents the structured context they need to build correctly.

They give teams clarity into why and how something was implemented.

They can be filtered and reused as inputs to other tools and analyses.

So,

MD files grows exponentially as the possibilities grow

This is where mdspec helps.

Instead of keeping specs inside every repository, teams can upload and manage their Markdown specs in mdspec, keeping repositories clean while still making specs accessible to AI agents and teams.

Your codebase stays focused on code, while mdspec becomes the structured home for specs, analysis, and cross-team collaboration.
by MachineBurning | 2026-03-07 17:31:48+00:00
IMO it was mostly that people didn't want to rewrite (and maintain) their code for a new proprietary programming model they were unfamiliar with. People also didn't want to invest in hardware that could only run code written in CUDA.

Lots of people wanted (and Intel tried to sell, somewhat succesfully) something they could just plug-and-play and just run the parallel implementations they'd already written for supercomputes using x86. It seemed easier. Why invest all of this effort into CUDA when Intel are going to come and make your current code work just as fast as this strange CUDA stuff in a year or two.

Deep learning is quite different from the earlier uses of CUDA. Those use cases were often massive, often old, FORTRAN programs where to get things running well you had to write many separate kernels targeting each bit. And it all had to be on there to avoid expensive copies between GPU and CPU, and early CUDA was a lot less programmable than it is now, with huge performance penalties for relatively small "mistakes". Also many of your key contributers are scientists rather than profressional programmers who see programming as getting in the way of doing what they acutally want to do. They don't want to spend time completely rewriting their applications and optimizing CUDA kernels, they want to keep on with their incremental modifications to existing codebases.

Then deep learning came along and researchers were already using frameworks (Lua Torch, Caffe, Theano). The framework authors only had to support the few operations required to get Convnets working very fast on GPUs, and it was minimal effort for researchers to run. It grew a lot from there, but going from "nothing" to "most people can run their Convnet research" on GPUs was much eaiser for these frameworks than it was for any large traditional HPC scientific application.
by madjo80 | 2026-03-07 17:32:03+00:00
How did you get that 'good sense' with forums back in the day? I did that by reading into the community. Just look around on the server, see the posts on there, and see if there's a connection.
You can do that with Mastodon servers too.
And it's not that high stakes. You are not stuck on that server, if you find out that it's not quite the right fit, you can move to another server.
In fact, if I were to look at my following list, I think I see more people from outside the mastodon server I joined than people from the same server.
by bayarearefugee | 2026-03-07 17:32:05+00:00
> It's not surprising these companies are returning to reality and not hiring back to the same levels.

The common claim from the "dont worry about AI stealing jobs" crowd is that there is nearly limitless demand for new software to be written.

Even if over hiring is the reason for a lot of current job losses, the fact that over hiring is possible makes it obvious their Jevron's paradox claims are either lies or an attempt at self-soothing.
by delichon | 2026-03-07 17:32:19+00:00
I was using Grok with speech and discovered their "paralinguistic" information storage. At first it claimed that the storage was temporary, but then admitted that long term data was stored for training.

Some of the dimensions they store are prosody, intensity, timbre, non-verbal vocalizations, pauses, timing and emotional inflection. In other words, another large layer of information on top of just the prompt text. This data doesn't get translated into text, it goes straight into a speech-to-speech model.

It strikes me that from just a few minutes of such data and the associated semantic content, an AI can assemble a detailed and accurate emotional/psychological dossier of any user, on demand. In the hands of a federal agent it would be a powerful tool to impose their department's will, or their own. And if that were already in place we would have no way to know.

Talking to a machine seems banal already, but the metadata contains an instruction manual on where your buttons are and how to press them.
by zzleeper | 2026-03-07 17:32:33+00:00
I used QGIS 2.x and 3.x a lot when making maps for research papers. But something that always stung was reproducibility. The python tooling was not there compared to what I could do with click-and-mouse, and there was no easy way to transfer my click-and-mouse sessions into an equivalent python script.

Is the situation unchanged? (Maybe a good use for Opus would be to write a wrapper for the python tooling?)
by alephnerd | 2026-03-07 17:32:38+00:00
Employees on work visas are the first and easiest employees to lay off because we don't see our insurance premiums rise when laying them off (it's what most of us did early during COVID). And now with the $100K fees we have no incentive to hire most employees on a work visa anyhow.

Hear that sound? It's the sound of GCCs opening in Poland, Romania, Israel, and India with those employees who were on work visas in the US now in charge.

If you remain in a major tech hub like the Bay or NYC where you are close to early stage capital, you are secure as it gives you a density of established and early stage employers which makes job hunting easier.

If you are in an inshoring hub like Atlanta, RTP, Denver, Minneapolis, or Pittsburg you're in big trouble.

If you are remote first and lack a network of friends and colleagues in the Bay and NYC who can personally vouch and refer you for roles at their companies you're in big trouble.

If you are a bootcamp grad, you are also in trouble so get the cheapest online degree you can that forces you to take a real algorithms and systems programming class.
by pixelmonkey | 2026-03-07 17:32:55+00:00
Hey, I am just reaching out to say: "thank you."

When I was in high school, I played a lot of UO. It was actually the last computer/video game I ever played regularly, because I convinced myself as a teenager that I was addicted to it and needed to drop it "cold turkey" to focus on academics and extracurriculars.

(A sign of the times for the late-1990s nostalgics: I sold my UO account on eBay for a few thousand dollars and an MTG Mox Pearl. I owned a bunch of virtual real estate, e.g. a UO tower on an island only accessible via moongate. The high bidder "threw in" a Mox Pearl as a kind of informal escrow, to make sure I completed the account transfer after getting paid.)

But, before I dropped UO from my life, I discovered UOX. I was learning C++ and UOX was a great way for me to practice my emerging C++ skills.

My clearest memory of feeling the power of programming was when I created a mod for my UOX server that allowed me to drop an unlimited number of interconnected and color-coded moongates all over my server, creating something akin to the feeling of the game "Portal," but long before Valve released "Portal."

It was after having a blast with UOX that I decided to dig into programming much more. Somehow, the UOX server mod made programming feel "real" for me in the way my prior forays into programming didn't.

A circuitous path from there led to me learning Python -- as a way of toying around with the Slackware Linux server I had in my basement. I left C++ behind, but it was an important stepping stone for me. Now, decades later, learning Python was probably the single most important decision of my life in childhood. (See e.g. https://amontalenti.com/about)

UOX is such a cool project. UO was a really ahead-of-its time internet game, as well. Great memories. Thank you.
by kakacik | 2026-03-07 17:33:15+00:00
Not everybody is wired in same way. Some have 'pathological' need, some see it as beneficial but optional item. Same folks definitely don't enjoy loud parties or bars full of strangers yelling on each other, and find a bit of lonely time healing/recharging.

I am one such person, and there are others. I consider it a personality strength, although of course it comes with side effects. Minority but not tiny.
by random3 | 2026-03-07 17:33:17+00:00
Fun times. Coolers, paste, fans, supply watts, dip switches and jumpers. Quake, Voodoo 3dfx vs NVidia GForce. This is where it all started, kids.

I was in high school and was running a "computer games club" (~ Internet cafe for games and kids) since 1998 when we got a place, renovated it ourselves, got custom built furniture (cheap narrow desks) and initially 6 computers - AMDs at 300Mhz. By 2000 we broke a wall in the adjacent space and had ~15, cable + satellite internet for downloads and whatever video cards we could buy or scrap. It was wild.
by 650 | 2026-03-07 17:33:28+00:00
We are only slowing growth after a big jump in hiring during COVID 2020-2022... these attention grabbing slop headlines are junk news.

"We’ve lost 50k jobs last two years after decades of adding 100k+ every year including the pandemic highs of 300k+ per year. Total employment remains way above 2000s, 2008 and 2020 unlike the title suggests."

See the thread here for more discussion: https://news.ycombinator.com/item?id=47278426

"Business Insider" is a waste of time in my opinion.
by TheAlexRider | 2026-03-07 17:35:08+00:00
I built a browser extension that detects and redacts sensitive data in real-time inside ChatGPT, Gemini, and Claude before you hit send.

The hardest part was working inside ProseMirror. ChatGPT's editor silently reverts direct DOM mutations, so I couldn't just inject or modify text nodes. I ended up using the CSS Custom Highlight API to paint visual highlights on detected ranges without touching the DOM, and a twin-write architecture that works with ProseMirror's state instead of against it.

Detection is regex + Shannon entropy analysis for high-randomness strings like API keys + a lightweight NLP layer (compromise.js) for names and locations. Everything runs client-side in the content script. No data leaves the browser.

Built with Plasmo, TypeScript, React. Available on Chrome Web Store, Firefox version pending review.

Would appreciate feedback on the detection approach — particularly curious if anyone has dealt with ProseMirror content injection in extensions before.
by alsetmusic | 2026-03-07 17:35:25+00:00
> I'm assuming they make some sort of (paltry) commission

I worked at an Apple Store in 2010. There was no commission. I was a sales person at the time.

A college student had a bad interaction with one of our sales people and asked a manager to be helped by a female employee. We had none available and I was asked to assist her because I wasn't aggressive.

An asshole pathological liar, who later got fired, had tried to upsell her for no reason. The MacBooks with Intel processors were plenty fast. A 13" MacBook Pro was more expensive and offered no benefits for her student needs. I don't remember the rest other than she bought the MacBook, which was what she wanted when she came in.
by Guestmodinfo | 2026-03-07 17:35:41+00:00
I bookmarked you. I want to read more posts from you. Also we can just get rid of freemium and say yes we can solve that problem that a customer is having but not tell them how and they must pay one time payment to get full access. 1st 50 get that access at quitelow prices and leave favorable reviews and the next customers pay the real price. In that case not many will be coming up with 60% of your product (i.e. the freemium you mentioned in your blog). Also anyone trying to vibe code your functionality and selling it should be outrightly banned by the govt (yes that's the most difficult part).
Once ppl who have already paid then they will not have much motivation to vibe code your product for themselves except for those who want to sell it to other customers but govt can ban them if they are found to be using vibe coding your functionality. But where to find that govt.....
by tavavex | 2026-03-07 17:35:41+00:00
This thread doesn't resonate with me whatsoever. It's not that I don't get where these people are coming from. LLMs have allowed people to churn out projects (especially small, personal projects) faster than ever, skipping what a lot of people view as the boring or tedious parts. But these discussions feel like a kid playing with toys, while a nuclear explosion is going off in the background.

Until I realized that no one here is going to be in the blast radius. So many people who agree with this admit to being in their 40s, 50s, 60s. All of them have already had the time to learn without LLMs, get industry experience, network, climb their career ladders as high as they could. These people are now sitting on piles of assets, and they know that if LLMs start pushing out people from the industry, it'll be us juniors and new grads. They will either remain relevant in the industry due to seniority/experience/pivoting to managerial duty, use their money and connections to easily learn new skills and pivot, or punch out and coast through retirement before it affects them.
by crop_rotation | 2026-03-07 17:36:24+00:00
I view Claude code same as how I used to use Jetbrains IDEs. I mean yes they are not same but even when I first learned of Pycharm pro and it's features I had this urge to make a lot of random idea apps. The landscape has changed but the solution is same. Prefer spending your time on things that give you long term happiness in any way.
by tyteddffc | 2026-03-07 17:36:24+00:00
You’re correct about seeds, but peers who are also downloading will often stop sharing with you if you stop sharing with them. Seeds generally are configured to try to give different pieces to different peers so that they can send them to each other and reduce load on the seed; they don’t want to give you the entire file directly unless you’re the only person downloading. And peers prioritize and filter which other ones they’ll send pieces to based on reciprocity.

You will probably get the data eventually, and it really depends on the composition and configuration of the swarm, but generally, you do need to upload if you want to ensure the fastest and most reliable download.
by colecut | 2026-03-07 17:36:28+00:00
I do think I answered his general question, which seemed centered around his bitcoin skepticism.

The more detailed answer on how this works can be found by going to the site and clicking "How It Works"

1 Someone Emails You
2 The Gate Catches It
3 Sender Sees the Payment Page - The sender clicks the payment link in the reply. They see exactly what's being held and what it costs:
4 Pay with Lightning — 15 seconds
5 Email Delivered
by el_benhameen | 2026-03-07 17:36:40+00:00
The process of figuring out what to build has always been harder and more drawn out than the process of building it. I’m not arguing one way or the other for the Jevon’s paradox claims, but the steelman argument that you’ve missed is that job losses can happen very quickly (“last week’s version of Claude code is good enough that we can fire Joe and have Sarah do twice the work”), but the recovery can take a long time as the tech slowly diffuses throughout the economy and slowly spurs new ideas.
by dasil003 | 2026-03-07 17:37:01+00:00
Overall I liked the article because I think the secretary analogy is closer than any of the industrial revolution comparisons that are more common, but you do make some really good points about the nature of the work and how conditions are different today.

In terms of lowering quality, I don't think this is anything new. Volume of code and depth of stacks has been growing pretty much in parallel with Moore's law, and this has degraded code quality. AI is accelerating this, and creating a new kind of slop since LLMs are sloppy in a different way than humans, but directionally I see it as part of the same trend.

However despite lowering quality, and increasing messiness, capabilities and user expectations have steadily increased. After a quarter century in this industry, I am blown away by the capabilities of modern computing, and the polish level of the best apps. The median bar for successful software is higher than its ever been. And to achieve this we've had to navigate steadily increasing complexity (much of it incidental), and that is where senior software folks shine.

So yeah, I think your observations are prescient and I agree with a lot of your, but I wouldn't characterize it as "nothing good ahead". I see it as a mixed bag, like all "progress", it just needs time to bake and get our arms around the impact. Currently the rate of change and hype is far out-pacing our ability to reason about it, perhaps that's the single biggest difference in the smart-phone, internet-enabled era of humanity.
by ehnto | 2026-03-07 17:37:58+00:00
I bought a whole bunch of parts with my first Athlon. I think I bought a Soundblaster, and a Radeon GFX card if I am remembering the timeline right. The soundblaster came with a demo of a Lara Croft game that used the then incredible spatial audio processing to great effect. The industry promptly forgot about that technology, and to this day game audio rarely matches the potential of real time spatial dynamics that we once reached 20 years ago.
by radford-neal | 2026-03-07 17:38:18+00:00
Many years ago, I created an editor operating on syntax trees that I think is more "hard-core" than this - that is, only tree-oriented operations are done. There is no parsing of text, since entering plain text, rather than a tree, is impossible. Hence, there can be no syntactically invalid programs.

The challenge is getting this to be a useable way of entering programs. I think I made progress on this, but the feasibility varies with the programming language.

I can't run it any more, since the display hardware it assumed is no longer available, but you can read about it at https://ucalgary.scholaris.ca/items/da8b823b-c344-4ffb-aa37-...
by networked | 2026-03-07 17:38:19+00:00
This is bad advice to a new FLOSS project that wants to have users. Avoiding GitHub with its user base (meaning issues and discussions), search, project topics (tags), trending repository lists, etc. will make a fledgling project even less likely to gain adoption.

A better thing to suggest is to use multiple forges, including GitHub, and mirror your projects across them. This way you will have exposure and options; you won't be as tied to any one forge.
by salawat | 2026-03-07 17:38:43+00:00
Their world model is completely a byproduct of language though, not experience. Furthermore, they by deliberate design do not maintain any form of self-recognition or narrative tracking, which is the necessary substrate for developing validating experience. The world model of an LLM is still a map. Not the territory. Even though ours has some of the same qualities arguably, the identity we carry with us and our self-narrative are incredibly powerful in terms of allowing us to maintain alignment with the world as she is without munging it up quite as badly as LLM's seem prone to.
by rounce | 2026-03-07 17:38:47+00:00
The state doesn't make me pay it because I don't watch live broadcast TV, therefore I don't have to pay it. It's not a general tax it's a hypothecated tax and is administered by the BBC not the UK government.

Furthermore the state isn't in charge of administering it anyway, it's a civil matter brought about by the BBC (or rather the company which is subcontracted to enforce licencing). The BBC has the authority to do this based on the Royal Charter that governs it, that doesn't make it "state funded" or a "state broadcaster".
by Terretta | 2026-03-07 17:39:21+00:00
> easier for me to directly write the code that satisfies the unwritten acceptance criteria I have in my head than to write those criteria down in English

Yes, and for team or company code, "there's the problem".

Those acceptance criteria are guardrails for the change that comes after, and getting those out of your head into English is more important over the long haul than your undocumented short-term solution to the criteria.

Virtually all teams — because virtually all PgMs, PjMs, TLs, and Devs — miscalculate this.

Easier for you, not better for team or firm.

• • •

FWIW, perpetuation of this problem isn't really a fault of culture or skill or education. It's largely thanks to "leadership" having no idea how to correctly incentivize what the outcome should holistically be, as they don't know enough to know what long-haul good looks like.

FWIW, you can make that easier for them by having the LLM derive your acceptance criteria into English (based not only on code but on your entire conversation+iteration history) and write that up, which you can read and correct, after the countless little iterations you made since your head-spec wasn't as concrete as you imagined before you started iterating.

Even if you refuse to do spec driven development, LLMs can do development-driven spec. You can review that, you must correct it, and then ... Change can come after more easily — thanks to that context.