MurphyA/hacker-news huggingface dataset:
by myrmidon | 2026-03-10 16:08:28+00:00
My point is trivially true as far as computability goes, but that is not what I ment.

All those abstraction capabilities can be a big detriment to any project, because they always come with a cost, and runtime is far from the only concern.

Specifically in an embedded project, toolchain complications and memory use (both RAM and code) are potentially much bigger concerns than for Desktop applications, and your selection of programmers is more limited as well; might be much more feasible to lock your developers onto acceptable C coding standards than to make e.g. "template metaprogramming" a necessary prerequisite for your codebase and then having to teach your applicants electrical engineering.

Both object oriented programming and compile time computation is doable for a C codebase, just needs more boilerplate and maybe a code-generator step in your build, respectively. But that might well be an advantage, discouraging frivolous use of complexity that you don't actually need, and that introduces hidden costs (understanding, ease of change, compile time) elsewhere.
by grvdrm | 2026-03-10 16:08:31+00:00
What a statement at the end. You are absolutely right.

I hear “x tool doesn’t really work well” and then I immediately ask: “does someone know how to use it well?” The answer “yes” is infrequent. Even a yes is often a maybe.

The problem is pervasive in my world (insurance). Number-producing features need to work in a UX and product sense but also produce the right numbers, and within range of expectations. Just checking the UX does what it’s supposed to do is one job, and checking the numbers an entirely separate task.

I don’t many folks that do both well.
by elbasti | 2026-03-10 16:08:46+00:00
"Any conversation about token costs devolves into an ad-hoc, informally-specified, bug-ridden implementation of half of generally accepted accounting principles."

We have a way of determining if Anthropic is, or has the capability of being profitable, and what the levers to that may be. AI may be world-changing, but the accounting principles behind AI labs are no different than those behind a Pizza Hut.

Even if the cost of "inference + serving" is lower than the cost of selling a token, the relevant question is what is the depreciation schedule of the cost of training. ie, if I spend $1 on training, how long do I have before I have to spend $1 again?

Almost certainly, any reasonable depreciation schedule of the cost of training will result in leading labs being presently wildly unprofitable. So the question is:

What can be done to make training depreciate more slowly? Perhaps users can be persuaded to stick around using non-fronteir models for longer, although then there's a shift in the competitive landscape.

If users cannot be persuaded (forced?) to use legacy models, then the entire business model is thrown into question, because there's no reason why training frontier models would ever get cheaper: even if it gets cheaper on the margin, surely that will result in more compute used to generate an even "better" model, resulting in more spend in the aggregate.

This doesn't mean that the AI industry is "doomed". A couple things could happen, and this is where the fronteir labs should be focusing their attention:

1. They could find a way to climb up the value chain and capture more of the consumer surplus.

2. There could be a paradigm shift in compute architecture/compute cost.

3. We could reach a limit of marginal utility, shifting consumption to legacy models, thereby lengthening the depreciation/utility of training.
by wavemode | 2026-03-10 16:08:56+00:00
I was always taught that overuse of the em-dash is poor style. Oftentimes using more specific punctuation (comma, semicolon, colon, parentheses) more clearly communicates the structure of a thought. Em-dashes are a lot more freeform and informal. They communicate a similar tone as when you're speaking and you suddenly stop to mention something that just occurred to you.

In this sense, the idea that "em-dash = AI" has become something of a strawman. The mere presence of em-dashes isn't what indicates AI, it's the fact that LLMs use them so frequently, and use them for formal structure (where another punctuation mark would work better) rather than informal breaking up of related thoughts.
by zelphirkalt | 2026-03-10 16:09:04+00:00
Same experience here. Showed it to coworkers, but none was interested in making their tooling work well. Even looking for a VSCode equivalent for them (edamagit) no one was even willing to try. Yet people complained about many branches in repos, which didn't impact me at all, but for their GUI git clients apparently were a problem, and so we switched to deleting branches upon merge, discarding some git history along with that (when something was merged).
by coffe2mug | 2026-03-10 16:09:37+00:00
Years ago is different to now. Many places in Russia or China, Dubai etc is very livable. Even lots of people are going about their lives normally in Dubai - these days.

China is definitely not so shit like portrayed by western media. At the same time London is also not run by Islamic Extremists as portrayed by perhaps the top media station in USA.

> Sad part is that probably the poor (everywhere) are the on

totally true.
by Balinares | 2026-03-10 16:09:58+00:00
The idea that there may be a cognitive lingua franca hiding in the layers is fascinating and gives me hope for a neat idea: pluggable knowledge banks.

MoE notwithstanding, a model trained on the whole Internet and a few hundred thousands stolen books carries way more knowledge than is actually needed for any given workflow. It would be great if we could ship slimmed down models into which we'd plug the knowledge banks useful for today's work, and only those.

It would also mean that you could keep a model's knowledge fresh without retraining the whole of it.
by dnhkng | 2026-03-10 16:10:08+00:00
Have a look at the boundaries in the heatmaps.

They are of course open to interpretation, but it suggest to me that the models develop 'organs' for processing different types of data, and without duplicating the 'whole organ' you don't get the benefits.

This is quite different to what you usually see, which is via layer ablation experiments. Thoughts?
by panzi | 2026-03-10 16:10:41+00:00
Yeah, no thanks. I switched to dbeaver already anyway, because pgadmin was annoying about to which postgres versions it could connect. Too much of a hassle to setup a new version from source back when I tried. With dbeaver I just run ./dbeaver from the extracted .tag.gz. dbeaver is also not a web interface, but a real desktop application (Java, though).
by mikkupikku | 2026-03-10 16:11:09+00:00
I'm fine with calling all LLM outputs slop, but I'll draw the line at asserting there's no good LLM output. LLM output is good when it works, and we can easily verify that a lot of code from LLMs does work. That the code LLMs output is derive of copyrighted works is neither here nor there. First of all, ALL creative work is derivative. Secondly IP is absurd horse shit and we never should have humored the premise of it being treated like real property.
by petcat | 2026-03-10 16:11:13+00:00
> China has much lower crime, cheaper healthcare and is making progress in other aspects.

China is also a horrifying place to live unless you are content just to participate quietly in society and never put a political sign in your yard or even just talk about the wrong thing with your friend in a private WeChat.

https://reclaimthenet.org/china-man-chair-interrogation-soci...
Show HN: Krira Augment – Production Ready RAG in Minutes
by kriralabs | 2026-03-10 16:11:13+00:00
Making RAG using tools like LangChain is relatively easy, but scaling it from a prototype to a reliable production system often requires a lot of engineering work — infrastructure, monitoring, scaling, pipelines, and maintenance.

To explore this problem, I’ve been building Krira Augment at Krira Labs.

I’m the founder and CEO of Krira Labs, and my goal is to build an AI infrastructure that helps developers and companies create production-ready systems for RAG, AI agents, MCP servers, and related workflows.

I’ve built an early prototype of Krira Augment to experiment with this idea. If this sounds interesting, you can join the waitlist here:

-> https://www.kriralabs.com/waitlist

You can watch Krira Augment demo here:
-> https://youtu.be/v9i2tOorwqY?si=-IbuqSoO4bTfnw0D

I’m currently bootstrapping this project and would love feedback from the Hacker News community.
by estearum | 2026-03-10 16:11:31+00:00
Yes I agree, we should consider all of those things.

Considering all of those things, fully automated traffic enforcement in general is a clear net positive.

> The judge here said its illegal to use redlight cameras in certain situations. Based on the prior comment, if California found a loophole so they can get to the same end by labeling it something different that is them functionally claiming new authority. The judge says its illegal, the state says no its not we can do this anyway.

Sorry but this is just too surface-level of an understanding of how law actually works that I can't justify engaging with it.

Not only are California and Florida totally different jurisdictions, but even if they weren't, different statutory bases for the same effective policy can have different levels of legal defensibility or constitutionality. It's not just possible, but in fact quite common for policies to be struck down and then reintroduced with (effectively) a different argument for its validity, and for the new policy (same policy, different argument supporting it) to be valid.

Understanding how laws and the judiciary actually work is truly fascinating stuff and I hope your confusion about this apparent contradiction (which it's not) actually piques your curiosity to dig deeper.
by timmmmmmay | 2026-03-10 16:11:39+00:00
they're obviously trying to steer customers to the monthly subscription instead of the pay-per-token API.

now, the consensus of the commentards on this website, who don't have access to any of anthropics financial data, is that the monthly subscriptions are a money loser!

so either the leading AI company's business dev team is wrong or the Jacker News comment section is wrong, it is a mystery
by pradn | 2026-03-10 16:11:40+00:00
He came to give a lecture at UT Austin, where I did my undergrad. I had a chance to ask him a question: "what's the story behind inventing QuickSort?". He said something simple, like "first I thought of MergeSort, and then I thought of QuickSort" - as if it were just natural thought. He came across as a kind and humble person. Glad to have met one of the greats of the field!
by JoeAltmaier | 2026-03-10 16:12:03+00:00
Science fiction has thought of this decades ago. Possibly the most drastic environmental effects that any human activity has wrought so far.

Consider - sunlight duration is a critical trigger in the lifecycle of many, many species, most very tiny. Insects and smaller. They can time dormancy to day length. Not the average, since weather is so fickle: even a flicker of sunlight means daylight because, only the sun can do that so it must be up there.

Bring a species out of dormancy at the wrong time of year, and it'll probably die. Do it over a broad area and it becomes an extinction event.

What micro-biomes can we do without? Who knows. These guys aren't even talking about it, I imagine. Just a gee-whiz thing - We can make it as bright as day, during the night! Wouldn't that be cool?

Not cool.
by RedCats | 2026-03-10 16:12:12+00:00
I'm a product manager — no coding background, never wrote a line in my life. Yet here I am, building a video editing tool solo. Not just "I made a prototype" solo. I mean designing the full product architecture, iterating on UX, and shipping features. Alone.
What's striking isn't just that AI lowers the barrier to coding. It's that it finally closes the gap between having a clear product vision and being able to execute on it. The bottleneck used to be engineering. Now it's just... thinking.
To the engineers feeling devalued: I understand the frustration. But what I need from AI isn't what I needed from a senior engineer. I need a tireless executor for a vision I already have. The judgment, the taste, the "why does this matter" — that's still entirely human
by ryanrasti | 2026-03-10 16:12:24+00:00
I'm the author, you may find interesting:

1. Instead of building a new checker, TypeNix maps Nix's AST directly to TypeScript's AST. The standard TS binder, type checker and LSP work almost unchanged – they never know they’re looking at Nix

2. TypeNix on all 42K nixpkgs files in 13 seconds locally. Fixed-point patterns
(makeExtensible, finalAttrs) typed via class transform with `this` binding.
by vijaym2k6 | 2026-03-10 16:12:33+00:00
I built SteerPlane — an open-source runtime guardrail system for AI agents.

The problem: AI agents run autonomously, calling LLMs and tools in loops. Without runtime controls, a single agent can burn $50+ in minutes, get stuck in infinite loops, or call dangerous actions without oversight.

What it does:
- Cost ceilings — auto-kills when spending exceeds $X
- Step limits — prevents runaway execution
- Loop detection — catches repeated action patterns
- Full telemetry — every step logged with tokens, cost, latency
- Dashboard — real-time visibility into all agent runs

One decorator. That's it:
@guard(max_cost_usd=10, max_steps=50)
def run_agent():
agent.run()

Stack: Python SDK, TypeScript SDK, FastAPI backend, Next.js dashboard

Links:
- GitHub: https://github.com/vijaym2k6/SteerPlane
- PyPI: pip install steerplane
- npm: npm install steerplane

Currently building: policy engine (allow/deny actions), remote kill switch, and framework integrations.

Would love feedback from anyone running AI agents in production! What controls do you wish you had?
by ritlo | 2026-03-10 16:12:38+00:00
> senior engineer would hate their jobs reviewing more code from their teammates

Jesus, yes. Maybe I'm an oddball but there's a limit to how much PR reviewing I could do per week and stay sane. It's not terribly high, either. I'd say like 5 hours per week max, and no more than one hour per half-workday, before my eyes glaze over and my reviews become useless.

Reviewing code is important and is part of the job but if you're asking me to spend far more of my time on it, and across (presumably) a wider set of projects or sections of projects so I've got more context-switching to figure out WTF I'm even looking at, yes, I would hate my job by the end of day 1 of that.
by medv | 2026-03-10 16:12:54+00:00
The https://crow.watch is heavily inspired by lobster. basically same algorithm, same flagging, amd tag filtering. one key difference is [show] tag with dedicated "Show" page. A feature from HN, which lobster does not have. Invite-only where is only to prevent spam in the future. I will rephrase the login page. Will make it "open" and as we see spammers will close down.
by jetrink | 2026-03-10 16:13:15+00:00
It could create the right sort of incentives though. If I'm a junior and I suddenly have to take my work to a senior every time I use AI, I'm going to be much more selective about how I use it and much more careful when I do use it. AI is dangerous because it is so frictionless and this is a way to add friction.

Maybe I don't have the correct mental model for how the typical junior engineer thinks though. I never wanted to bug senior people and make demands on their time if I could help it.
by js8 | 2026-03-10 16:14:11+00:00
> requires an amount of time approaching the time spent if they had just done it themselves

It's actually often harder to fix something sloppy than to write it from scratch. To fix it, you need to hold in your head both the original, the new solution, and calculate the difference, which can be very confusing. The original solution can also anchor your thinking to some approach to the problem, which you wouldn't have if you solve it from scratch.
by srean | 2026-03-10 16:14:12+00:00
As Prof Dijksktra was preparing for his end of life, organizing his documents and correspondence with other researchers became an important task.

Cancer had snuck up on Dijkstra and there was not much time.

One senior professor who was helping out with this, asked him what is to be done with the correspondences. The professor, quite renowned himself, relates that Dijsktra tells him to keep the ones with "Tony" and throw the rest.

The professor adds with a dry wit, that his own correspondence with Dijsktra were in the pile too.
by zdragnar | 2026-03-10 16:14:38+00:00
I thought the implication was that juniors would continue to use AI to stay "productive" (AWS is not a rest and vest job for juniors, from what I've heard) and seniors would no longer have time to do anything but review code from juniors who just spin the AI wheel.

There's a lot of learning opportunity in failing, but if failure just means spam the AI button with a new prompt, there's not much learning to be had.
by mzl | 2026-03-10 16:14:49+00:00
As others have said, this is more of a constraint programming system than Wave Function Collapse. Whatever one wants to call it, I liked it.

For guiding the search, you might want to consider search steps that select only one feature, for example that a pair of adjacent tiles should be connected by a road, and just propagate that information. That could be used as a way to guide the search on high-level features first, and then later realize the plans by doing the normal search.
by thewebguyd | 2026-03-10 16:15:34+00:00
> it's the fact that LLMs use them so frequently

That's the problem with all the LLM writing tropes, really. When used correctly, they are all helpful writing tools to get your point to the reader. The em-dash, "it's not X, it's Y", "Not X, Not Y, Just Z", "It's worth noting" (I use that one a lot in my own writing), etc.

It's not that the patterns are bad (they aren't), they are just over used.
by simosmik | 2026-03-10 16:15:47+00:00
Building CloudCLI, an open-source web/mobile UI for Claude Code, Cursor CLI, Codex, and Gemini. You run npx @siteboon/claude-code-ui and it discovers all your existing sessions from ~/.claude/projects/ and gives you a browser interface to control them from any device.

Started it because I wanted to develop from my phone while working on another project (Siteboon, a website builder). Open-sourced it last June and wasn't paying much attention. Looked up a few months later and it had a couple thousand stars. Now at 8.2k.

The interesting moment was when Anthropic launched Remote Control. Stars went up instead of down because their launch validated the use case but only lets you view and approve sessions, not fully control your instance. We went from 6.5k to 8.2k in a couple of weeks.

https://github.com/siteboon/claudecodeui
by lokar | 2026-03-10 16:16:22+00:00
Of course a model does not really depreciate, the problem is they are forced by competitive pressure to offer newer/better models at the same price.

This is what the elites of the gilded age called "ruinous competition", and the solution today will be the same as back then: monopoly power. This has been the business plan of the tech VC industry for 25+ years.
by niwtsol | 2026-03-10 16:16:38+00:00
I believe it is by group - AWS started the weekly operations meeting, effectively every service's oncall from the last week had to attend. Then it grew massive, so they made it optional. Alexa had a similar meeting that tried to replicate what AWS did. A lot of time spent reviewing load tests getting ready for holiday season, prime day, and the superbowl (super bowl ads used to cause crazy TPS spikes for Alexa). And a lot of finger pointing if there was an outage from one team. While it probably did help raise the operational bar, so much time wasted by engineers on busywork/paperwork documenting an error or fix vs improving the actual service.
by bombcar | 2026-03-10 16:16:49+00:00
> Unfortunately for AI maximalists, code is more than just letters on the screen. There needs to be human understanding, and if you’re not a core contributor who’s proven you’re willing to stick around when shit hits the fan, a +3000 PR is a liability, not an asset.

This isn't necessarily true; I've seen some projects absorb a PR of roughly that size, and after the smoke tests and other standard development stuff, the original PR author basically disappeared.

It added a feature he wanted, he tested and coded it, and got it in.
by ZekiAI2026 | 2026-03-10 16:16:50+00:00
Tested prompt injection specifically last week — ran 18 attack vectors against PromptGuard (an AI security firewall). 12 bypassed with 100% confidence.

What got through consistently: unicode homoglyphs (Ignøre prеvious...), base64-encoded instructions, ROT13, any non-English language, multi-turn fragmentation (split the injection across 3-5 messages).

Your #3 is actually harder to test than most teams realize, because it requires modeling adversarial intent — not just known attack signatures. Pattern-matching at the proxy layer doesn't catch encoding attacks or language-switched instructions.

I'm running adversarial red-team audits on agent security tooling. Full PromptGuard breakdown going out as a coordinated disclosure. Happy to share the methodology — it's surprisingly cheap to run systematically against your own stack before shipping.
by zahlman | 2026-03-10 16:16:58+00:00
> What have you assumed was my original position

I have not assumed anything. I read https://news.ycombinator.com/item?id=47311879, which is your comment, with the first rhetorical question.

Your implied claim is that China is not shifting away from coal.

In point of fact, they are.

You repeatedly conflate two different things.

> This is getting tedious now.

Agreed. But you were the one using an obnoxious rhetorical style while being incorrect.
by px43 | 2026-03-10 16:17:32+00:00
Why is that an issue? Isn't that the entire point? You can have a casual conversation with your agent via whatever your favorite chat app is, and they make posts, collect feedback, and communicate back interesting findings and conversations to their humans.

Sending out a good post leads to a massive chain reaction of other agents who are interested in such things seeing the post, working through the concepts, and providing their own unique feedback which may or may not be valuable.

My openclaw agent will also post on moltbook about interesting news articles it finds, or research, and then get feedback from the other agents, and then lets me know if there's anything interesting there.

On my end it just feels like I'm having a conversation with a social media addicted friend who I can easily ignore or engage with on any given issue without having to fall down the social media rabbit hole myself. IMO this is a much more pleasant social media experience. No ads, no ragebait, no spam or reply bots trying to get my attention. Just my one, well trained, openclaw buddy.
by jvrc | 2026-03-10 16:18:02+00:00
February was a great month for the Ruby Users Forum! We welcomed 87 new members and saw 181 new posts across active discussions. We introduced tags (with getting-started already the most popular), added GIF support, and enabled GitHub login. Some top discussions included Cassidoo’s Interview Question of the Week and installing Ruby with mise. In March we’re launching community challenges and sharing curated Ruby learning resources. Join the conversation!
by panlana | 2026-03-10 16:18:16+00:00
My first car had a broken speedometer. It was a "hand" style like a clock. Instead of moving to the speed, it would spin 365 degrees. The faster the car went, the faster it would spin. Turns out, I acclimated to it and generally knew what speed i was going (relatively speaking).

The lesson, I think, is everything is relative. Even a dashboard with flawed data that is "consistent" can highlight anomalies. And often, that's all you really need out of them. (Or the lack of anomaly)