MurphyA/hacker-news huggingface dataset:
by tcaxle | 2026-02-09 12:09:49+00:00
This is fun! I put my (slightly oddly setup) system into it but I couldn't reconfigure which set of speakers were connected to which amp, or reorder the signal chain at all. Is this a planned feature? E.g. I have an integrated all-in-one amp that drives my main speakers but I tap off the pre-amp output into a secondary integrated amp that drives two secondary sets of speakers but your app assumed that my second amp was driving all six speakers and so spat out a warning about power levels...
by locknitpicker | 2026-02-09 12:09:54+00:00
> This is a good thing. I don’t need to focus on oil refineries when I fill my car with gas. I don’t know how to run a refinery, and don’t need to know.

No, it isn't. If you do not know what the project does, you are unable to even review the changes proposed by a coding agent.

Consequently, we already have a long track record of LLMs introducing vulnerabilities.

LLMs are great at speeding up small tasks but the trade-off is that developers become progressively clueless.
by jmalicki | 2026-02-09 12:10:15+00:00
That sounds like stacked changes (if you're not familiar think how lkml patches are like 0/8 1/8 etc where each is a standalone change that only depends on ones before), and I have been using agents create sets of stacked PRs when I have a big diff.

Instead of ordering of files, it creates an ordering of PRs where each has descriptions, independent CI, etc. and can be merged one at a time (perhaps at the small cost of the main branch having unused library functions until the final PR is merged)
by tombh | 2026-02-09 12:10:53+00:00
Wow, glad you had fun exploring. It suddenly made me think of a little feature that I'm not sure we made the best job of exposing. In the little trophy icon toggle on the right, there's the Top Ten list of views, then under those there's a little line that just says "In current viewport: 123km". Did you see that? Did it make sense? I implemented it, so of course I know that it's better than clicking all the points around a peak to find the longest view from a mountain summit. But maybe it's not obvious to other users? What I do is zoom in so that the viewport only contains the area of the summit (or indeed entire country for that matter) that I'm interested in, then I look at that "In current viewport:" line without having to click anything.

So using that, I would say that the longest line of sight in North America is from Mount Rainier, at 390km, looking North West into Canada: https://map.alltheviews.world/longest/-121.76853942871094_46...
by ordu | 2026-02-09 12:11:46+00:00
> Must be great to work with people like him who have infinite patience and composure.

It is not just patience, he is ready to spent a shitload of time explaining basics to strangers. Such an answer would take, I believe would take a very least half an hour to compose, not counting the time you need to read all the relevant discussion to get the context. But yeah, it would be great to have more people like him around.
by tifa2up | 2026-02-09 12:11:52+00:00
https://agentset.ai/

Open-source RAG infrastructure.Every team I talk to has the same experience: RAG works in the demo, breaks in production.

We handle ingestion through retrieval with optimizations baked in. 97.9% on HotpotQA vs 88.8% for standard RAG. Model-agnostic, 22+ file types, built-in citations, MCP server. MIT licensed.

https://github.com/agentset-ai/agentset
by illuminator83 | 2026-02-09 12:12:30+00:00
It's not really about the implementation of Java (might be bad, I don't know).
It is the specification.

- People talked about null being an issues and that is a big one.

- The entire idea of OOP extremism Java implemented was a mistake - though just a consequence of the time it was born in. Much has been written about this topic by many people.

- Lacking facilities and really design for generic programming (also related to the OOP extremism and null issue

So much more more you can find out with Google or any LLM
by lossolo | 2026-02-09 12:12:33+00:00
> Plenty of researchers do think so and claiming consensus for your position is just false

Can you name a few? Demis Hassabis (Deepmind CEO) in his recent interview claims that LLMs will not get us to AGI, Ilya Sutskever also says there is something fundamental missing, same with LeCunn obviously etc.
by mlrtime | 2026-02-09 12:12:39+00:00
Who's moral justification? Yours?, My families?, my community?, my government? my god?

I maybe too much of a individualist, so I get a little triggered when I see claims from others about the moral justification of what I should eat, what job I should have, who I should vote for... When these things that I do are not hurting myself or other humans.

Now I'm sure you could take an example of each one of these and "butterfly affect" to some example of hurting another human, but I could do the exact same thing to any one of [your] lifestyle choices.
by seyz | 2026-02-09 12:13:09+00:00
I built this because running OpenClaw locally felt a bit like running chmod 777 for the internet.

While Docker/VMs provide OS-level isolation, they don't solve the application-layer risk: if my agent hits a Prompt Injection on a malicious site, it can still use its authenticated tools to wipe my CRM or exfiltrate Slack data.

ClawBands is a middleware that hooks into the OpenClaw before_tool_call event loop. It enforces a synchronous blocking check before any dangerous operation (Shell Exec, File Write, etc.) is actually executed.

Ideally, this acts like sudo for your agent:

In Terminal (TTY): It pauses execution and renders an interactive prompt.

Headless: It can route approval requests via a dedicated tool (clawbands_respond) to Telegram/WhatsApp.

It's a 24h PoC written in TypeScript. I'm particularly interested in feedback on the blocking logic implementation, handling the async pause reliably in the event loop was the trickiest part.

Happy to answer any questions!
by jama211 | 2026-02-09 12:14:43+00:00
This article has some serious usage of either bad prompting, or terrible models, or they’re referencing the past with their stories. I have experience AI’s deleting things they shouldn’t but not since like, the gpt4 days.

But that put aside, I don’t agree with the premise. It doesn’t make the hard parts harder, if you ACTUALLY spend half the time you’d have ORIGINALLY spent on the hard problem carefully building context and using smart prompting strategies. If you try and vibe code a hard problem in a one shot, you’re either gonna have a bad time straight away or you’re gonna have a bad time after you try and do subsequent prompting on the first codebase it spits out.

People are terrible observers of time. If you would’ve taken a week to build something, they try with AI for 2 hours and end up with a mess and claim either it’s not saving them any time or it’s making them code so bad it loses them time in the long run.

If instead they spent 8 hours slowly prompting bit by bit with loads of very specific requirements, technical specifications on exactly the code architecture it should follow with examples, build very slowly feature by feature, make it write tests and carefully add your own tests, observe it from the ground up and build a SOLID foundation, and spend day 2 slowly refining details and building features ONE BY ONE, you’d have the whole thing done in 2 days, and it’d be excellent quality.

But barely anyone does it this way. They vibe code it and complain that after 3 non specific prompts the ai wasn’t magically perfect.

After all these years of engineers complaining that their product manager or their boss is an idiot because they gave vague instructions and demanded it wasn’t perfect when they didn’t provide enough info, you’d think they’d be better at it given the chance. But no, in my experience coaching prompting, engineers are TERRIBLE at this. Even simple questions like “if I sent this prompt to you as an engineer, would you be able to do it based on the info here?” are things they don’t ask themselves.

Next time you use ai, imagine being the ai. Imagine trying to deliver the work based on the info you’ve been given. Imagine a boss that stamped their foot if it wasn’t perfect first try. Then, stop writing bad prompts.

Hard problems are easier with ai, if you treat hard problems with the respect they deserve. Almost no one does.

/rant
by jacquesm | 2026-02-09 12:15:09+00:00
Oh that is so cool. I played the one in Liepaja, Latvia for a bit and it was absolutely amazing. It's love/hate for me (like the harpsichord), I love the instruments but I usually do not like the music that is played on them because of the grating effect. I have pretty bad tinnitus which really spoils a lot of music for me, extremely annoying.
by mrkeen | 2026-02-09 12:15:14+00:00
I lean on types heavily as my vehicle for change.

My UserService doesn't know that it's talking to a UserDB (ironically I learned this from Uncle Bob).

All UserService knows is it has a dependency which, if passed a UserId, will return a User (+/- whatever the failure mode is .. Future<User>? Promise<User>? ReaderT m User?)

When I change my mind about what UserService requires or what UserDB provides (which I frequently do), I immediately look at all the red underlines that my compiler & static types tell me about.
by chaz6 | 2026-02-09 12:15:23+00:00
Are there any passkey hardware tokens the private key is effectively irretrievable? That is why up to now FIDO U2F has been my preferred additional factor. The down side is that you have to register multiple tokens for each authentication service in case one is lost or damaged. I miss the days of openid when I could use my own idp with any service, but the walls quickly went up when the big players wanted to control the ecosystem.
by MrGilbert | 2026-02-09 12:17:57+00:00
> If you study game theory even a little one of the big lessons is that cooperation at scale is _incredibly_ hard

I never realized that game theory would give me an answer to that question. You can tell that cooperation at scale is really hard just by observing the discourse around climate change and the necessary steps, as it is something that basically involves everyone. Thanks for the hint!
by KempyKolibri | 2026-02-09 12:18:26+00:00
As I understand it there's no good evidence that n3:n6 ratio matters, _as long as both are at adequate levels_. Studies showing the ratio to be of concern achieve a "low n3:n6 ratio" by low n3, rather than high n6.

Eggs are believed to lead to adverse outcomes because of:
1. Their high cholesterol content.
2. Their SFA content.

I'm not sure what you mean by cholesterol being rebutted. The only thing like that I'm really aware of is the dietary guidelines de-prioritising dietary cholesterol, but that decision was made because when making DGs, people want to focus on the biggest levers we can pull. Dietary cholesterol _does_ have a negative impact on health, but it also has a threshold effect at around 400mg/d after which it has considerably less impact (unless you're part of the ~20% of the population who are "cholesterol hyper responders").

Because most people eating a SAD are already at that threshold, the decision was made to take dietary cholesterol off the headline recommendations, but if you read the details in the DGs and the meta-analyses that drive them, they still point to lowering dietary cholesterol as a smart health move.

I frequently see this change portrayed as "no longer recommending the lowering of dietary cholesterol" or "admitting they were wrong about dietary cholesterol", but that's not really what happened.
by abbadadda | 2026-02-09 12:19:01+00:00
ComputerPoker.ai

We trained PyTorch models on solved poker scenarios for post-flop, turn, and river situations.
The planned "killer feature" is to give users feedback on their poker play in the flow of a simulated poker tournament or simulated cash game scenario. The goal is to play against "GTO Bots" (Game Theory Optimal Bots) to learn how to play closer to GTO.^1

Poker has been a passion of mine for a few years now, I find the game incredibly intellectually stimulating as well as a tremendous catalyst for personal growth, and this project has been a great way to channel that energy.

The web app uses Django/Channels/WebSockets. We've built an internal discounted CFR solver as well, hopefully building up to multiway scenarios in the future. The webapp is still in Beta/gated, and you're interested in learning more please email contact at surlesol dot com.

We are thinking of pricing $8/month or $74.99/year, with the rationale that this will be far less expensive than learning by experience at even micro stakes for online poker, with better feedback for learning, and at least we make it explicit that you're competing against bots ;-)

1. I am aware that GTO play is not always optimal, especially in live poker where live tells are available, and often exploitative strategies fare better than pure GTO. The target audience for ComputerPoker.ai is not hardcore poker pros, there's plenty of existing software for that, but rather those individuals looking to get acquainted with what GTO play "feels like." Then, with this knowledge in hand, knowing what the GTO play would be given various assumptions about our range and a reasonable opponent's range, we can deviate from the GTO play as deemed necessary.
by iso1631 | 2026-02-09 12:19:14+00:00
Training seems fine. I learn how to write something by looking at example code, then write my own program, that's widely accepted to be a fair use of the code. Same if I learn multiple things from reading encyclopedias, then write an essay, that's good.

However if I memorise that code and write it down that's not fair use. If I copy the encyclopedia that's bad.

The problem then comes into "how trivial can a line be before it's copyrighted"

def main():
print("This is copyrighted")
main()

This is a problem in general, not just in written words. See the recent Ed Sheeran case - https://www.bbc.co.uk/news/articles/cgmw7zlvl4eo
by mrtksn | 2026-02-09 12:19:45+00:00
I kind of agree that "America First" policies tend to be Europeanization type policies and as a result quite un-American and that's also why USA will end up like Europe if it keeps course.

Europe is great in many ways but lacks the dynamism exactly because of its highly controlled immigration policies instead of free market ones. Bureaucrats actually are terrible at picking who should come. A major example are the Turkish immigrants to Germany, where they imported huge numbers of Turkish immigrants for their booming car industry in the 60s and instead of just treating them like normal people they did this "guest worker" thing and as a result those Turks failed to integrate and remained in the low socioeconomic status with exception for some high profile cases like the inventors of the mRNA vaccine or the Crysis founders. In other places like UK or USA, Turkish immigrants tend to have much higher socioeconomic status.

If EU end up doing its chip and energy industry push, better be following the pre-Trump era immigration policies because that's how USA got is all the workforce that make USA leap ahead in many industries. Some French or Swedish immigration officer would not be picking people better than industrialists or startup founders. Immigration and its integration are not Europe's strong traits.
by codethief | 2026-02-09 12:20:20+00:00
> If you make the specs detailed enough so that there's no misunderstanding possible: you've just written code, what we already do today

This was my opinion for a very long time. Having build a few applications from scratch using AI, though, nowadays I think: Sometimes not everything needs to be spelled out. Like in math papers some details can be left to the ~~reader~~LLM and it'll be fine.

I mean, in many cases it doesn't really matter what exactly the code looks like, as long as it ends up doing the right thing. For a given Turing machine, the equivalence class of equivalent implementations is infinite. If a short spec written in English leads the LLM to identify the correct equivalence class, that's all we need and, in fact, a very impressive compression result.
Show HN: Shippable – Lovable but with live dev environment (Django+Next)
by royatthreesigma | 2026-02-09 12:20:22+00:00
I was being asked to fix a lot of Lovable projects for prod and it was painful because it was a messy codebase. So I built shippable where people can vibe code in an opinionated stack with live dev environment so the result is more predictable.

Current setup is not elegant (stringed along on django + drf + nextjs + shadcn + digital ocean droplets + docker compose). But I found it was much easier for the llm (Claude) to do a cleaner job when it had the dev environment available and has real runtime feedback.

Took me a while to build it over January, but I want to know what you think.

Link: https://app.shippable.build/

There’s a signup + free credit limit to prevent abuse. If you want more credits lmk here and I can add them manually.
by aurareturn | 2026-02-09 12:21:09+00:00
Maybe I can't. But that's also why I'm invested into AI companies right now.

Plan:

1. Keep my job for as long as I can by leveraging current AI tools to the best of my ability while my non-AI user colleagues lose earnings power or their job

2. Invest my money into AI companies and/or S&P500

3. If I'm truly rendered useless, live off of the investment

You got any better ideas? How would you do this?
by rich_sasha | 2026-02-09 12:21:18+00:00
EU has a solid path of a lot of money to be spent in the next 5-20 years. Chips, AI, advanced weaponry, more advanced weaponry etc. If there was a program where everyone gets a slice, I'm sure it would work - a bit like ESA. It is doing it piecemeal that runs into the very problem you describe.
by m00dy | 2026-02-09 12:21:35+00:00
X-Ray Feed – A Chrome extension to visualize the Twitter/X algorithm

I got tired of guessing why my timeline looked the way it did, so I built a tool to reverse-engineer the "Heavy Ranker" logic in real-time.

It’s an MV3 extension that overlays the hidden weight of every post directly in the feed. It distinguishes between organic content ("Thunder" nodes) and AI-injected recommendations ("Phoenix" nodes) so you can actually distinguish following vs. algorithmic fill.

The scoring is based on a log10(Engagement) * 20 formula to visualize velocity. I originally built it just to clean up my own feed hygiene, but it turned out to be a pretty useful arbitrage tool, identifying "flops" (good topics from big accounts that failed due to structure) that are worth rewriting.

All the analysis happens locally in the browser. Would love to hear what you think about the scoring accuracy.

https://xrayfeed.deepwalker.xyz
Ask HN: Cloud Agnostic Business Systems
by thorin | 2026-02-09 12:21:37+00:00
As a follow-up on other related threads I had my first interaction where a major European company stated that they want to go down a route where they can switch cloud provider easily if required. After the last few years of building on serverless systems on Azure/AWS this seemed to be a big U-turn for me. We'll look to go back to deploying our systems on Kubernates containers. Note the majority of the work I'm doing is integrations between different internal and external systems for enterprises.

I was surprised to hear them call out explicitly that this was due to lack of trust and stability in US providers. Normally when you hear something like this it's not an isolated incident but a trend. Of course we hear about this in the news, but it's the first time I experienced it directly.
by einkaufspilot | 2026-02-09 12:21:40+00:00
I built this because I hated the daily “what should we cook?” loop.

Einkaufspilot takes one natural-language prompt (example: “2x pasta, 1x fish, 1x vegan, surprise me”) and generates a practical week plan plus one consolidated grocery list.

What’s live right now:

* interactive demo on the landing page
* recipe URL import
* automatic ingredient deduping for one list

I’m still early and iterating quickly.
Would love feedback on:

* clarity of the core flow
* whether the output feels useful enough for weekly use
* what’s missing before this would replace your current meal-planning workflow

Demo: https://einkaufspilot.app
by jrjeksjd8d | 2026-02-09 12:22:05+00:00
It feels like every cloud product I use is accumulating more of these peripheral features I don't want, while the core functionality is stagnant or even degrading. I'm assuming this is a Conway's Law situation where the company has to grow, and they hire more devs, but those devs can't all work on the core product so they make new greenfield stuff instead.

Until we stop chasing endless growth for it's own sake we're doomed to be stuck these enshittified products.
Show HN: Questle – Daily Mindful Side Quests That'll Make You Say What?
by andrewspode | 2026-02-09 12:22:16+00:00
A friend and I made this project (with a little help from Claude, naturally).

We wanted to create a wordle-esque shared experience, so everyone gets the same quests and those quests should have some meaningful impact on your day.

The approach we took was to create around 100 sentence structure templates that used a selection of verb and noun arrays. These were nested so depending on the sentence you might want all "things" (a very large list) or perhaps more granular like "things.furniture".

We had multiple categories/sub-categories and put around 100 words in each, giving us millions of possibilities - more than enough for selecting 9 each day for a while.

The outcome is some really quite surreal quests - hence the tagline, 'daily mindful side quests that'll make you say "what?"'

I have personally found them to be quite useful. They stop and make you think, doing quite mundane things with a mindful lens (like "appreciate a pot you might usually ignore"), or stretching yourself to do something new.

When I sent it to a friend, one of the quests was to "make a pizza from scratch". Several hours later, he messaged me saying that he had caved as it was the last quest on his list, so he did it and felt better for it.

So nothing crazy from a technical perspective going on here (except perhaps denying the thought of simply having AI create the quests for us) but definitely something worth sharing IMO!
by api | 2026-02-09 12:22:20+00:00
Climate change is a great example of a horrid game theory problem. Solving it requires an all cooperate pact as long as fossil fuels remain one of the easiest cheapest ways to get power. As long as that’s true, any defector can outcompete everyone in industrial production and creating a higher standard of living.

The other way to beat this is to advance renewable or nuclear power or both to the point that these options are cheaper than fossil fuels, which changes the game by making defection much less profitable.
by windexh8er | 2026-02-09 12:23:01+00:00
But say the obvious part out loud: Sam Altman's agenda should not be a person that you want to amplify in this type of platform. This is why Sam is trying to build Facebook 2.0: he wants Zuckerberg's power of influence.

Remember, there are 3 types of lies: lies of commission, lies of omission and lies of influence [0].

https://courses.ems.psu.edu/emsc240/node/559
by jeroenhd | 2026-02-09 12:23:08+00:00
Antivirus programs will run on PowerShell scripts, VBScript files, JScript files, and all other kinds of automation on Windows.

The screenshots from the article clearly show a permission prompt for a program. Whether that's a binary or a shell script or something else doesn't matter, the infection stage should've been caught by anti malware rather than permission prompts.

Windows Defender does this already. If Apple's AV can't catch this, I think they may be relying on their DRM-as-a-security-measure (signatures, notarisation, etc.) a bit too much.