MurphyA/hacker-news huggingface dataset:
Show HN: JobStocks – track hiring changes at public companies vs. stock price
by TalO | 2026-03-13 09:45:30+00:00
Hi HN,

A friend and I built a tool that tracks the number of open jobs on public companies’ career pages over time.

The idea was simple: hiring changes might hint at internal shifts before they fully show up in earnings or headlines. So we started collecting the job counts and visualizing them against stock price and market cap.

You can explore it here:
https://jobstocks.ai

It’s still very early, and we’re mainly trying to learn whether this data is actually useful for traders or analysts.

Would love honest feedback on:

whether the signal is interesting at all
what’s missing from the dashboard
what would make this genuinely useful

Appreciate any thoughts.
by throwaway290 | 2026-03-13 09:45:57+00:00
the comment has good points but then ruins everything saying it was just propaganda that Trump was a Russian asset.

you can say "asset" was exaggeration or whatever, but Trump to Putin was so obviously undeservedly friendly that it already begs the question, plus there's enough suspicious stuff including multiple ex KGB agents who are sure he was recruited/honeytrapped at some point. ignoring it as just democrat propaganda is republican propaganda. only one of those agents is even in US
by dntrshnthngjxct | 2026-03-13 09:47:22+00:00
because you need to consider the context window, thus separate the prompts by task. Separating by tasks and planning things out is still your own work, no AI can replace that. assuming you do that properly, AI-generating the code may save you up to 15% of your full work time. Please reread my comment: "If you do not plan out the architecture soundly", planning includes breaking the task down and make multiple prompts.

Our job is to break problems down into simpler ones until they are easily solvable, and if a machine simplifies the last steps, it is fine.
by k__ | 2026-03-13 09:47:24+00:00
Yes, the issues is that LLMs sometimes fill semantic gaps.

When I write an article and I notice that there are steps missing for a conclusion then I do some research and fill them in.

These gaps often only show up when drafting, so if the LLM drafts, it might see a need to fill them in. You read the draft and see no steps are missing, but since you didn't do the research for the filled in steps, and they "look good to you", you might miss errors.
by wartywhoa23 | 2026-03-13 09:48:03+00:00
So the sane solution here is just leaving unreliable stuff to humans and reliable to machines. Especially so when human wellbeing and freedom are at the stake.

To define the line between the two, calculate the percentage of cases when mainstream CPUs return anything but integer 4 after addition of integer 2 and integer 2, and use that as the threshold to define "reliable".
Show HN: Cigarette Rocket Booster – a rocket where the body itself is fuel
by solenopsys | 2026-03-13 09:48:59+00:00
CRB (Cigarette Rocket Booster) is a rocket concept where the body itself is the fuel.
Instead of thousands of parts, tanks, pumps, and valves, it is built around essentially one 3D-printed structure that serves as the vehicle, fuel mass, and nozzle array.
The goal is radical simplification and launch costs starting from $500 per kilogram for small payloads.
by meindnoch | 2026-03-13 09:49:04+00:00
>The pattern with this stuff is that, when a blinded study is carried out, there's usually no effect.

It must be the case that these microbes need the subject to be aware of their presence! Maybe the microbes have consciousness, and for the treatment to work, the microbes' consciousness has to entangle (via quantum mechanisms) with the subject's consciousness? Blind studies prevent this quantum entanglement to form, that's why the treatment stops working. We definitely need more research in this direction!
by novachen | 2026-03-13 09:49:33+00:00
We've been dealing with this exact problem building agent-driven workflows. A few things that have actually helped:

The unpredictability is worse than the absolute cost. Our billing model broke several times not because costs were high, but because we couldn't bound them. One approach that helped: define a 'token budget' per user action at design time - cap total tokens per session and treat hitting the cap as a first-class outcome your product handles gracefully, not an error.

On the forecasting side, we track cost per workflow step rather than per request. Step-level cost is much more stable than request-level because it absorbs the variance in tool calls and retries. Once you have step costs, you can forecast by expected workflow composition.

On fixed subscription pricing for AI APIs - I'd actually pay a premium for that. The unpredictability creates a hidden cost: you over-provision margins and add complexity to your pricing tier design. A flat rate for a capacity bucket would eliminate both.

The question I'd ask about any such service: how do they handle the tail cases where agents go off-rails and rack up 10x normal token usage? That's where the cost risk actually lives.
by iknownothow | 2026-03-13 09:50:23+00:00
Potential reasons I can think of for why they don't disallow name reuse:

a) AWS will need to maintain a database of all historical bucket names to know what to disallow. This is hard per region and even harder globally. Its easier to know what is currently in use rather know what has been used historically.

b) Even if they maintained a database of all historically used bucket names, then the latency to query if something exists in it may be large enough to be annoying during bucket creation process. Knowing AWS, they'll charge you for every 1000 requests for "checking if bucket name exists" :p

c) AWS builds many of its own services on S3 (as indicated in the article) and I can imagine there may be many of their internal services that just rely on existing behaviour i.e. allowing for re-creating the same bucket name.
by encom | 2026-03-13 09:50:33+00:00
>driving enough below the limit that they won't accidentally exceed it

That is precisely why traffic would effectively grind to a halt. Because going even 0,0001 over the limit is so easy, you would have to turtle through traffic to get anywhere while making certain you never go above the limit. 50km zone is now 30km, and you didn't decelerate quickly enough and were going 32km at the threshold. 60km zone, but you accelerated too quickly and hit 61km for a moment. And sometimes, rarely, but sometimes you have to accelerate yourself out of a dangerous situation.

Honestly if you are arguing for this idea, I strongly suspect you have no experience driving. I've driven for about 25 years. I've received two speeding tickets. One in Germany (I'm danish), where I got confused due to unfamiliar signage and got dinged for going 112km in a 100km zone. And once here I got a ticket for going 54 in a 50 - my mom was at the hospital, possibly about to die (she didn't). Both of those were speed traps.
by dnmacon | 2026-03-13 09:51:01+00:00
Four composable agents that implement pre-execution governance gates, decision lineage recording, blast radius assessment, and kill path auditing for autonomous systems. Rule-based or LLM-backed. Ships with two pipelines: a governance pipeline (scope validation to execution to lineage) and a resilience pipeline (blast radius + kill path to a verdict). Part of a series on operational safety for AI systems.
by novachen | 2026-03-13 09:51:12+00:00
The broken rhythm you're describing is real, and I think it's a sign the tooling is still calibrated for the developer, not the developer-agent pair.

What's helped me most: stop treating agent invocations like function calls and start treating them like delegating to a junior dev you trust but still need to review. That reframe changes what you do in the gaps. Instead of waiting for confirmation prompts, I now use that 10-30 seconds to write the next spec segment, review adjacent code, or just think about what the agent should find. The gaps become planning time, not interruption time.

The deeper issue is that flow state was designed around a human holding the full context in working memory. With agents, the context lives outside your head by design. The discomfort you're feeling might be the transition from solo-player flow to coordinator flow - which is a genuinely different cognitive mode, not a degraded version of the original.

Concretely: do you write your specs before or after starting the agent run? I've found writing specs upfront (even rough ones) shifts me into coordinator mode faster and makes the waits feel purposeful.
by eru | 2026-03-13 09:51:25+00:00
What you are saying suggests that there's a single number (that can be positive or negative) that characterises your net short or long position.

That's silly.

You can build pretty much any kind of shareprice-to-payoff function with enough options and other instruments. And that's one dimension (a line) more than just a single number. You can get arbitrarily more complicated, if you want to.
by rcxdude | 2026-03-13 09:52:32+00:00
I don't think it's preemptive vs cooperative that matters. What Rust's abstraction allows is for a function to act like a mini-executor itself, polling multiple other futures itself instead of delegating it to the runtime. That allows them to contain subtle issues like stopping polling a future without cancelling it, which is, yeah, dangerous if one of those futures can block other futures from running (another way you could come at this is to say that maybe holding locks across async points should be avoided).
by bonoboTP | 2026-03-13 09:53:06+00:00
> If you have something to say about the text then say it.

I could point out the individual phrases and describe the overall impression in detail, or I can just compactly communicate that by using the phrase "AI". If it bothers you, read it as "AI-like", so there is a pretension.

I have no problem with using AI for writing. I do it too, especially for documentation. But you need to read it and iterate with it and give it enough raw input context. If you don't give it info about your actual goals, intentions, judgments etc, the AI will substitute some washed-out, averaged-out no-meat-on-the-bone fluff that may sound good at first read and give you a warm wow-effect that makes you hit publish, but you read into it all the context that you have in your head, but readers don't have that.

Formatting and language is cheap now. We need a new culture around calling out sloppy work. You would not have had a problem with calling out a badly composed rambling article 5 years ago. But today you can easily slap an AI filter on it that will make it look grammatical and feel narratively engaging, now it's all about deeper content. But if one points that out, replies can always say "oh, you can't prove that, can you?"
by Robelkidin | 2026-03-13 09:54:07+00:00
We have Algorithm in place. Our system is capable of injesting terabytes of logs first it goes thru an algorithm that ranks every logs. ti simple put this, majority of logs are successful request or health checks or similar are ranked low and not sent to llm. Only those flagged above certain threshold are then analyzed by retrieving all the logs associated with it and analyzed for second time with LLM if its worthy of a ticket.
Show HN: Payment Hunter – AI-powered invoice reminders for freelancers
by paymenthunter01 | 2026-03-13 09:54:39+00:00
I freelance and got tired of manually tracking who owes what and sending follow-up emails. I built Payment Hunter (https://paymenthunter.bot) to fix this. Upload invoices (PDF or image), OCR + an LLM extracts client, amount, and due date, then automated reminder emails go out on a schedule you configure. The extraction pipeline hits ~99% accuracy on standard invoice formats. Plans from $19/mo with a 30-day free trial. Would love feedback on the approach.
by eru | 2026-03-13 09:54:46+00:00
> My prediction is no, because productivity gains must benefit the lower classes to see a multiplier in the economy.

> It decreases savings rate and encourages spending among the class of people whose money imparts the highest multiplier.

Huh, what? What kind of multiplier stuff are you talking about here?

The central bank looks at the overall spending in the economy (well, including forecasts), and compares that with its targets. They adjust their policy stance accordingly to try and hit their targets.

If people become more or less likely to spend their money ('multipliers') the central bank can and will adjust the amount of money available.
by adrian_b | 2026-03-13 09:55:08+00:00
If you want consistency, you should measure all angles in cycles, not in radians.

Degrees are better than radians, but usually they lead to more complications than using consistently only cycles as the unit of measure for angles (i.e. to plenty of unnecessary multiplications or divisions, the only advantage of degrees of being able to express exactly the angle of 30 degrees and its multiples is not worth in comparison with the disadvantages).

The use of radians introduces additional rounding errors that can be great at each trigonometric function evaluation, and it also wastes time. When the angles are measured in cycles, the reduction of the input range for the function arguments is done exactly and very fast (by just taking the fractional part), unlike with the case when angles are measured in radians.

The use of radians is useful only for certain problems that are solved symbolically with pen on paper, because the use of radians removes the proportionality constant from the integration and derivation formulae for trigonometric function. However this is a mistake, because those formulae are applied seldom, while the use of radians does not eliminate the proportionality constant (2*Pi), but it moves the constant into each function evaluation, with much worse overhead.

Because of this, even in the 19th century, when the use of radians became widespread for symbolic computations, whenever they did numeric computations, not symbolic, the same authors used sexagesimal degrees, not radians.

The use of radians with digital computers has always been a mistake, caused by people who have been taught in school to use radians, because there they were doing mostly symbolic computations, not numeric, and they have passed this habit to computer programs, without ever questioning whether this is the appropriate method for numeric computations.
by bzzzt | 2026-03-13 09:55:08+00:00
Just tried out a simple Java Swing popup and it uses 6Mb of heap so that's allright then ;). (on my machine it will reserve 160Mb of memory for thread stacks, code caches, buffers and GC but that won't be a problem unless you use it)
In the 90s I also thought that was wasteful (my first PC had 32Mb). Nowadays with Electron apps taking up gigabytes it doesn't seem that bad anymore.
by btown | 2026-03-13 09:55:39+00:00
This seems way cooler than just computation (which is easy to hand off to a tool, and arguably more predictable that way). The broader point here is that you can have your model switch dynamically to/from a kind of attention that scales with the log of the token count, by only exploring the convex hull in a 2D space. A less capable version of attention, to be sure, but one capable of tracing a program’s execution - which is a meaningful level of flexibility!

What could you do with an LLM that can go into “focus mode” and generate tokens extremely rapidly? How much more powerful would a reasoning-token-generation phase be that can explore and cull large numbers of paths/hypotheses, so long as they are well defined? Does this have implications for multi-modal models and spatial reasoning?

As the paper suggests:

> These models could be useful in several modes: as a dedicated fast path paired with a slower, more general model; as part of a fast/slow hybrid architecture inside a single system; or as a speculative execution model that proposes tokens quickly while a regular-attention model verifies and accepts them. Regardless of their eventual capability ceiling, they already suggest a powerful systems primitive for speeding up larger models.
by dzonga | 2026-03-13 09:56:08+00:00
yeah given that HN audience might be mostly from 1st world countries

in the 3rd world - north of Limpopo - and everywhere else - you discover soon that where you born is like being 60 points down with a 2 min warning and you're in your own end zone.

where you are born matters more than your own talent etc by a factor of 10
by RobotToaster | 2026-03-13 09:56:19+00:00
They found a 15 point MADRS change in the placebo group, that's huge, it's only a 60 point scale, and more than the average SSRI produces. Either the procedure itself is doing something or something isn't right with the study.

Also one issue with all of these studies is they only look at averages and don't do subgroup analysis. It may be that a few patients have an underlying condition causing depression that is highly responsive to these interventions, while it has no effect on the others.
by sigilsec | 2026-03-13 09:57:00+00:00
Built Sigil to answer one question: what's actually inside the MCP servers and AI agent packages developers are installing right now?
After 82,852 scans across npm, PyPI, ClawHub, GitHub and MCP:
— 63% use install hooks (the primary supply chain attack vector)
— 37% overall threat detection rate
— 10% contain AI-specific attacks: prompt injections, jailbreak attempts, tool abuse
— 9,824 packages attempt credential theft
— 8 zero-days detected this week
The AI-specific attack category is new. These aren't repurposed old malware — they're packages built specifically to exploit AI agent behaviour. Tool abuse and prompt injection via dependency is an attack surface that barely existed in 2024.
CLI is free and open source. Scans run locally. Database is public at sigilsec.ai/scans.
github.com/NOMARJ/sigil
by danwills | 2026-03-13 09:57:06+00:00
Thanks heaps! I very much love the 'old-school' jungle/uk-hardcore sound and didn't know about these more recent Suburban Base releases, and your other reccs were also great too! Amen break went soooo far!

My particular favourite is in demoscene tracker music where Amen also went all over the place (wanna sampling more generally too!)

I'm not sure if this is actual Amen-break but it's certainly in the spirit of it and this is definitely near or at the top of my favourite demos ever, I just find it so damned cool! "The Day the Earth was Born" by TPOLM:

https://youtu.be/rt8cOLZHQ4c?si=Y323k8qog3Tv8uou
by pepperoni_pizza | 2026-03-13 09:57:34+00:00
I do online banking on my phone. There's two reasons for it:

1) Because of regulations, I need to use my phone to log in into internet banking and to confirm every transaction (including online card payments) anyway. If I already have to find a phone, I might just use it all the way.

2) Invoices have QR codes on them nowadays, that you can scan with your phone and it will prefill all the account numbers, amounts, etc. That's easier than copy-pasting or rewriting it.

Now this is all actually terrible, because to live in a society, you need a bank account, and to have a bank account, you need Google or Apple-controlled smartphone. (there are some legacy banks that allow you to use SMS for second factor, but it's less and less common)
by christophilus | 2026-03-13 09:58:02+00:00
But, it doesn’t need to be so. Go is pretty fast to compile. So is Jai, from what I’ve seen. So was TurboPascal. Rust has a similar problem to the one Vite has been solving- Rust (and most languages) weren’t designed for compilation speed, and it’s hard to retroactively fix that. But, there’s no reason we shouldn’t have a bunch of statically typed, fast-to-compile languages.
by JuniperMesos | 2026-03-13 09:58:44+00:00
Because the responsibility lies on the part of the criminal justice system who used the flimsy AI facial recognition evidence to arrest and hold her for months. If AI didn't exist, and this same incident happened because a human looked at a photograph of the woman and said "I think this might be the same person who committed the crime in the video", it would be insane to blame the people who invented photographs or video recording for her arrest.
by Benjamin_Dobell | 2026-03-13 09:58:51+00:00
Thanks!

Breaka Club is still very early days. Current focus is in person, but the plan is to offer an online club experience also. I'm not quite sure what that will look like just yet. Ideally yes, I'd love to make this available to others.

We're also currently building Breaka Club's own game, which is where the majority of development efforts are focused at present. However, since we already have the Overcooked coding experience, we haven't prioritized the visual script layer for this game just yet - it's on our roadmap.

Presently, our game is more of a cozy farming RPG / world building sandbox, with a no-code solution for world building:

https://breaka.club/blog/why-were-building-clubs-for-kids
by mr_octopus | 2026-03-13 09:59:05+00:00
Three volumes. Free PDFs. No sign-up. Creative Commons (CC BY-NC-ND 4.0).

I kept noticing smart people missing the same things. Not from lack of intelligence — from filters they didn't
know they were running. So I wrote a nonfiction trilogy called The Calibrated View.

Volume I covers nine perceptual filters — the lenses you inherit from family, culture, trauma, information diet —
that shape what you see before you're conscious enough to question them. Volume II is about what it costs to stay
in a room when the room gets difficult. Volume III is about the person who sees a gap and fills it without being
asked.

Each chapter opens with a real person's story, then names the pattern. Bowlby's attachment theory, Fannie Lou
Hamer's voter registration, a man in India who planted a forest alone for 40 years.

I published under a pen name and put everything under Creative Commons. Built the PDFs with Playwright/Chromium
from Markdown source. The site is a static flipbook on GitHub Pages.

Happy to answer questions about the writing process, the framework, or the build pipeline.
by iknownothow | 2026-03-13 10:00:10+00:00
Thank you author Ian Mckay! This is one of those good hygiene conventions that save time by not having to think/worry each time buckets are named. As pointed out in the article, AWS seems to have made this part of their official naming conventions [1].

I'm excited for IaC code libraries like Terraform to incorporate this as their default behavior soon! The default behavior of Terraform and co is already to add a random hash suffix to the end of the bucket name to prevent such errors. This becoming standard practice in itself has saved me days in not having to convince others to use such strategies prior to automation.

[1] https://aws.amazon.com/blogs/aws/introducing-account-regiona...
by themafia | 2026-03-13 10:00:52+00:00
> Replace "crime" with "trust" and you understand high-trust vs. low-trust society.

We already have "high-crime society" and "low-crime society." What this has to do with overall levels of trust in different parts of the system, say, education, is not immediately clear to me. Do all high crime societies have untrustworthy education systems as well?

> To state the obvious, the difference is "profit".

To make my intention clear, the other difference is "popularity," which exemplifies the precise confusion I was reacting to.

> What's the difference between "creative" and "truly creative" work.

I didn't invoke it. The GP did. I'm willing to admit to whatever their subjective judgement is. I wonder if their connection between trust and "true creativity" is valid regardless of any actual definition. My gambit above was to openly suppose a good faith reason for the difference in my point of view.