MurphyA/hacker-news huggingface dataset:
by rafaelmn | 2026-03-12 22:20:43+00:00
> The "no LLM" stance makes sense if you don't have guardrails. With the right constraints, AI-assisted code is faster AND safer than solo human development — because the agent never gets tired, never rushes before a deadline, and never thinks "I'll test that later."

Ironically I had a bunch of cases recently where CC would stop saying stuff like "this test problem is unrelated/a pre-existing issue when it had no proof of this and it was clearly not true (the branch built/tests were passing before the LLM changes).
by SsgMshdPotatoes | 2026-03-12 22:20:45+00:00
Nice idea! Em dashes were giveaways for AIs and typos for human, at least in the ones I did, so those are at least trivial. So might have to do some filtering at least for those.

Some were hard though, yeah (at least if not looking longer than 5-10 seconds). Btw, it seemed more logical to me to just see a green/red card when you click, i.e. right choice or wrong choice. Getting red for the correct answer confused me a bit (but this might just be me).
by simoncion | 2026-03-12 22:20:49+00:00
What's the advice on ULAs? On my internet-connected VLANs, I have a -er- site-local IPv4 subnet, a unique local IPv6 subnet, and a global IPv6 subnet. This works just fine.

Does the "advice" boil down to "You should NEVER use ULAs and ALWAYS use GUAs!" and is given by the same very, very loud subset of people who seemed to feel very strongly that IPv6 implementations should explicitly make it impossible to do NAT?
by fakedang | 2026-03-12 22:20:50+00:00
Yay, we got one ship to cross the straits!

VS

We could have an entire Indian-owned port, outside the straits in question, with an attached O&G pipeline that we paid for, connected directly to the oil and gas fields in Iran. Not to mention all the rare earth minerals in Afghanistan that we had received sanction to mine prior to the war, that would also have been shipped through this port.

The cognitive dissonance in nationalist Indians is honestly tiresome and unsurprising at this moment.
by cortesoft | 2026-03-12 22:21:00+00:00
I have some lawyer friends, who work as internal council to companies, that are already experiencing this.

People are cranking out legal requests and claims with LLMs and sending them to companies. Almost all of them are pretty much meaningless, and should be ignored.

However, they legally can't just ignore them. They have to have someone review the claim, verify that it is bullshit, and then they can ignore it. That takes time, though.

So people can generate and send millions of legal claim instantly, but the lawyers have to read them one by one.

The asymmetry of effort is huge, and causes real issues.
by lowenbjer | 2026-03-12 22:21:57+00:00
I know that feeling. Just because a tool is good doesn't mean you enjoy using it.
I moved deeper into streaming infra with Python, C/C++, Go, and funnily enough Elixir. Then a complete path change into fintech and later AI/ML, which meant a lot of JavaScript/TypeScript and reluctant Python. I appreciate the Python ecosystem but find the language itself ugly to read and write. Always a last resort for me.
Today it's mostly TypeScript, Go, and Lua.
by jackvalentine | 2026-03-12 22:22:01+00:00
> Sounds like whoever is scheduling meetings need to adapt to a new asynchronous environment whereas many meetings isn't necessary.

I agree, and a lot of my 'participation' in these meetings these days is read the papers, write my opinion, attach it to the documents and tell people I'm not attending.

That said we're 5 years in to this thing and people haven't adapted.
by alan_sass | 2026-03-12 22:22:05+00:00
I've seen these data poisoning attacks from multiple perspectives lately (mostly from):
SEC data ingestion + public records across state/federal databases.

I believe it is possible to reduce the data poisoning from these sources by applying a layered approach like the OP, but I believe it needs many more dimensions with scoring to model true adversaries with loops for autonomous quarantine->processing->ingesting->verification->research->continue to verification or quarantine->then start again for all data that gets added after the initial population.

Also, for: "1. Map every write path into your knowledge base. You can probably name the human editors. Can you name all the automated pipelines — Confluence sync, Slack archiving, SharePoint connectors, documentation build scripts? Each is a potential injection path. If you can’t enumerate them, you can’t audit them."

I recommend scoring for each source with different levels of escalation for all processes from official vs user-facing sources. That addresses issues starting from the core vs allowing more access from untrusted sources.
by hedora | 2026-03-12 22:22:07+00:00
I’ve found this happens with repos over time. Something convinces it that implementing the same bug over and over is a natural next step.

I’ve found keeping one session open and giving progressively less polite feedback when it makes that mistake it sometimes bumps it out of the local maxima.

Clearing the session doesn’t work because the poison fruit lives in the git checkout, not the session context.
by vidarh | 2026-03-12 22:22:52+00:00
I've spent 30 years seeing the junk many human developers deliver, so I've had 30 years to figure out how we build systems around teams to make broken output coalesce into something reliable.

A lot of people just don't realise how bad the output of the average developer is, nor how many teams successfully ship with developers below average.

To me, that's a large part of why I'm happy to use LLMs extensively. Some things need smart developers. A whole lot of things can be solved with ceremony and guardrails around developers who'd struggle to reliably solve fizzbuzz without help.
by quzr | 2026-03-12 22:23:10+00:00
I kept running into the same problem with AI coding tools: repo context setups are scattered across docs, gists and random repos.

Things like CLAUDE.md files, Cursor rules, Copilot instructions, AGENTS.md, hooks, skills, monorepo splits, etc.

So I started collecting repo patterns in one place to compare different setups and see what actually works in real projects.

Right now there are some seed patterns across Claude Code, Cursor, Copilot and Windsurf.

Curious what repo structures others here are using.
by piiritaja | 2026-03-12 22:23:46+00:00
I mean humans communicate the same way. We don't interpret the words literally and neither does the LLM. We think about what one is trying to communicate to the other.

For example If you ask someone "can you tell me what time it is?", the literal answer is either "yes"/"no". If you ask an LLM that question it will tell you the time, because it understands that the user wants to know the time.
by dzhiurgis | 2026-03-12 22:23:52+00:00
Apple could win a lot of likes if they added some form of storage expansion. Even a recessed USB-C for those tiny drives would go a long way.

Doesn't need to be super fast or fancy, just extend the life of device a little more.

Soldered internal storage and ram is fine if I can store my non-essentials in a cheap drive. Or my essentials in a way that is recoverable if device fails. iCloud helps for photos and families, but it's still far too slow if you don't live near it.
by protocolture | 2026-03-12 22:24:19+00:00
Depends. The only predictions I have seen here are the centaurs vs anti centaurs of Doctorow, and even his analysis I find pretty flimsy.

I dont think the race to shove an LLM into everything is going to grow the pie.

But I also dont think it is impossible that a use case will present itself that will create further jobs.

The issue is that its largely unpredictable.

Its a bit like, we are sitting around in the 1950s trying to predict how computers will affect the economy.

It is going to take more than 1 successful deductive leap to get us from 1950s computing -> miniaturisation -> computer in every home -> internet communications.

Every deductive leap we take is extremely prone to being wrong.

We simply cannot lie back and imagine every productive relationship in the economy and then extrapolate every centaur and anti centaur possible for it.

What we do know is that theres a bit of a gold rush to effectively brute force every possible AI variant into every productive relationship in the economy. The fastest way to get the answer to your question is to do it. Possibly the only way to get the answer is to do it.

For instance, someone might imagine LLMs simply eating a whole bunch of service industry jobs. At the same time, theres a mid state where it eats some, but the remaining staff are employed to monitor the LLMs to prevent them handing out free shit to smart shoppers. Its also easy enough to imagine that LLMs never quite get there and the risk is too large for foul play, so they just dont gain that kind of traction. Its also possible to imagine an end state where LLMs can get to 0% risk if they are constantly trained on human data coming from humans doing the same job, and that humans are gainfully employed in parallel with LLMs. Its possible that LLMs are great at business as usual, but the risk emerges when company policies change, and the cost of retraining LLMs makes it impractical for move fast and break things companies to do anything but hire humans. My favourite scenario is one where humans are largely AI assisted, trained on particular people, and theres a massive cybercrime industry built around exfiltrating LLM training weights trained on high functioning humans and deploying them without humans to the third world to help them get 80% of the quality of first world businesses, making them heavily competitive.

We dont know what we dont know.
by fakedang | 2026-03-12 22:24:44+00:00
India agreed to capitulate on the Iranian port investments before the US-Israeli invasion, when Trump was playing the tariff games. If a growing economy can be subverted and forced to act against its interests, is it really a superpower at that point?

Guess the US Deputy Secretary was right when he stated that they'll never make the same mistakes with India that they made with China.
by andriy_koval | 2026-03-12 22:24:55+00:00
> Virtually nothing happened in decades

it was decades of very intense proxy wars: Yemen, Syria, Iraq, Gaza, Lebanon. Iran didn't hesitate to attack oil assets: https://en.wikipedia.org/wiki/Abqaiq%E2%80%93Khurais_attack

> Is this what the "western world" is about? Securing resources by bombing people preemptively because they might do something you don't like one day?

sure, that's what humans do through centuries. If you don't do it, you get extinct because other forces become stronger and bomb you.
by HelloMcFly | 2026-03-12 22:25:07+00:00
What am I supposed to be reading here? The article? The short snippet of commentary about it? The back-and-forth comments on the commentary?

Your link seems to have nothing to say about inequitible school quality based on unfair, racist, classist propety tax funding models. How about this one which followed cohorts for 40 years and found substantial differences in life outcomes correlated* to school funding levels (PDF ALERT!): https://gsppi.berkeley.edu/~ruckerj/QJE_resubmit_final_versi.... Crucially this looks at life outcomes, not just test scores.

---

*Just in case someone wants to remind me or anyone else that correlation does not equal causation, I will say "I know" and "in longitudinal studies, time operates as an exogenous variable that adds substantial evidence of causality in well-designed research.
by roncesvalles | 2026-03-12 22:26:24+00:00
The benefit from having a 5% better product that hundreds of millions of people will use is worth the duplicated effort in the beginning. The numbers just make sense.

>If this were seven government funded teams solving the same problem

The problem here is "government funded" - the trials are not rationalized by free-market economics. That is, a 5% better product in the end would not be worth seven competing developments initially.
by alexwebb2 | 2026-03-12 22:26:33+00:00
Wow. The guy who’s been thanklessly maintaining the project for 10+ years, with very little help, went way out of his way to produce a zero-reuse, ground-up reimplementation so that it could be MIT licensed... and the very-online copyleft crowd is crucifying him for it and telling him to kick rocks.

Unbelievable. This is why we can’t have nice things.
by BosunoB | 2026-03-12 22:26:42+00:00
The whole idea of just sending "no" to an LLM without additional context is kind of silly. It's smart enough to know that if you just didn't want it to proceed, you would just not respond to it.

The fact that you responded to it tells it that it should do something, and so it looks for additional context (for the build mode change) to decide what to do.
by itishappy | 2026-03-12 22:26:44+00:00
> Can't you fucking do your homework beforehand, think your idea thoroughly, and then have at least a small written paragraphs about it before interrupting your colleagues.

They never said they didn't.

> Really, I am not a co-processor in a bus for you to dispatch a job to me and raise an interrupt line whenever the fuck you fancy doing it.

I am! I'm perfectly capable of managing my own time and shoeing others away if needed. Please bother me! That's why I have a cell phone and a salary.

Almost certainly relevant: I work in manufacturing.
by alan_sass | 2026-03-12 22:26:46+00:00
I think an interesting thing to pay attention to soon is how there are networks of engagement farming cluster accounts on X that repost/like/manipulate interactions on their networks of accounts, and X at large to generate xyz.

There have been more advanced instances that I've noticed where they have one account generating response frameworks of text from a whitepaper, or other source/post, to re-distribute the content on their account as "original content"...

But then that post gets quoted from another account, with another LLM-generated text response to further amplify the previous text/post + new LLM text/post.

I believe that's where the world gets scary when very specific narrative frameworks can be applied to any post, that then gets amplified across socials.
by readitalready | 2026-03-12 22:26:57+00:00
People really need to stop saying Trump is worse than Kamala/Biden on Palestine.

Biden and the Democrats erased Palestine. There is nothing anymore that Trump could do about it. He can't resurrect the dead. Everything happened because of Democrats, not Trump.

Voters are very rational. They know that Democrats were the bad guys. It's why they currently have a 17% approval rating.

Let's all focus on removing the rest of the Democrats from power and replace them with true anti-Israel candidates. That's the only hope for a modern society.
by derefr | 2026-03-12 22:27:22+00:00
Insofar as the thing we're talking about here isn't exactly "hack-back" per se, but more like "booby trapping your honeypot", I think you might be able to make an argument analogous to the one that would apply as a booby-trap defense:

Namely, that if "common sense" is enough to prevent someone from suffering any injury from a booby trap even when they do trigger it, then it's not really a "booby trap" in the classical definition. It's just an object with dangerous edge-cases.

In the literal booby-trap case, you might picture, say... a garden hose.

It would be hard to imagine someone being harmed by "normal" use of a garden hose. Most ways to engage with it wouldn't result in any harm. You could turn it on, maybe get a bit wet or lashed if the hose whips around as it stiffens. Point it at yourself and use it to wash yourself clean. Maybe point it in your mouth and choke.

The only clear way to harm yourself with a garden hose, would be to put the hose in your mouth and then turn it on. And then to not remove the hose when you begin to feel very, very uncomfortable.

And that's very silly! Why would you do that? You could have stopped drinking from the hose at any time!

A garden hose has a dangerous edge-case: the water stream is infinite, and the hose fits in your mouth, and the internal stomach capacity of a human is finite. But it's an absurd dangerous edge-case. Nobody with common sense would encounter this edge-case. So a garden hose is not a booby trap. And an abandoned house with a garden house connected to a water supply, is not a booby-trapped house.

See what I'm getting at here?

You can give up and stop streaming (/ parsing / building-up-your-in-memory-ADT-from) an HTTP response that "just keeps going and going" at any time. And any vuln-scanning client programmed by someone with some common sense (e.g. a professional security researcher) would have that common sense built into it. So a 1TB .env-file HTTP response is not a booby trap.

And yet, of course, it will catch (and break) those "special" clients, built by people with no software-engineering common sense, i.e. script kiddies. But it's not your fault that some people have built deranged software that goes around wrapping its mouth around strangers' garden hoses!
by epistasis | 2026-03-12 22:27:28+00:00
Yes, it's going to look bad, and Jan 6 was just a trial run. Now all those criminals that have been freed are in the ranks of a supposed "police" force that self-equips from US Patriot Tactical.

But there's not enough of them. Even for Minneapolis, a mid-size city. There might be a few targeted attacks, lots of voter intimidation, but the US is a very big place, and the ranks are too small, and their popularity is tiny compared to other authoritarian regimes.

It's going to be ugly, maybe really really ugly with violence and innocent voters hurt, but the forces of democracy will win out. Minneapolis shows that there's a strong backbone to this country still, even if some swing voters were tricked.
by Anamon | 2026-03-12 22:27:29+00:00
The problem is that

A. People want to connect with other people, not talk to computers, and

B. AI slop peddlers know this and have an incentive to lie about their content.

If GenAI content was always reliably declared and people's choices were respected, we wouldn't have a problem.

It's like saying, what does it matter if the news article was fake, as long as you enjoyed reading it? It matters because when I read the news, I want to read about things that actually happened, not stories that manage to fool me into believing they're true.
by singron | 2026-03-12 22:28:02+00:00
This is very funny. I can see how this isn't in the training set though.

1. If you wanted it to do something different, you would say "no, do XYZ instead".

2. If you really wanted it to do nothing, you would just not reply at all.

It reminds me of the Shell Game podcast when the agents don't know how to end a conversation and just keep talking to each other.
by kjellsbells | 2026-03-12 22:28:10+00:00
you're giving me flashbacks to my time at Microsoft where a one night trip to another state meant hours wrestling with EY's filing system to record the trip and quizzical questions from my accountant about why Microsoft paid $0.23 to South Carolina for my taxes.

IIRC it really got going in the pandemic when states realized that all these knowledge workers were earning nice money and not paying a cent in taxes to the state they had run to to get away from the virus.
Show HN: Hugoifier – convert any HTML template to a Hugo and Decap setup via AI
by ragelink | 2026-03-12 22:28:43+00:00
I built Hugoifier to solve a problem I kept running into: simple projects have existing HTML templates or want a simple website, but setting up Hugo properly (layouts, partials, hugo.toml, content structure) plus wiring in a git-native CMS takes real time even when you know what you're doing.

Hugoifier automates the full pipeline:
1. Analyze – inspects an HTML theme or existing Hugo theme for structure
2. Hugoify – uses an LLM to convert raw HTML into valid Hugo Go templates
(baseof.html, partials, index layouts)
3. Decapify – generates a Decap CMS config.yml auto-tuned to the site's content
structure, with whitelabel support

The output is a deployable Hugo site + CMS, ready to push to GitHub and serve from Cloudflare Pages or GitHub Pages.

Why Hugo + Cloudflare: no database, no server, statically compiled HTML served from the edge. Practically unhackable, infinitely scalable, nearly free to host.

Supports Anthropic (default), OpenAI, and Google backends. MIT licensed.

pip install hugoifier
hugoifier complete themes/my-theme

GitHub: https://github.com/ConflictHQ/hugoifier
Docs: https://hugoifier.dev
by XCSme | 2026-03-12 22:29:24+00:00
To be honest, I had this "issue" too.

I upgraded to a new model (gpt-4o-mini to grok-4.1-fast), suddenly all my workflows were broken. I was like "this new model is shit!", then I looked into my prompts and realized the model was actually better at following instructions, and my instructions were wrong/contradictory.

After I fixed my prompts it did exactly what I asked for.

Maybe models should have another tuneable parameters, on how well it should respect the user prompt. This reminds me of imagegen models, where you can choose the config/guidance scale/diffusion strength.
by davorak | 2026-03-12 22:29:37+00:00
One example of voice is of retreading old ground over and over, taking a long time to give evidence or get to the point. Content expressed with this voice is hard to extract from the text.

Another voice might add citations to every little detail to the point that it is hard to read, but makes a great reference and/or starting point for additional research.

Voice is not really separate from content, in part it is the choices of what content to include.
by anoushaj | 2026-03-12 22:29:52+00:00
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We are building the next foundation layer for enterprise AI.

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by bink | 2026-03-12 22:30:29+00:00
DESQview was absolutely not crashy. I ran several different types of BBS software in it without issues. The "DESQview (or worse...)" comment raised the hair on the back of my neck. DESQview was revolutionary at the time and I was annoyed at having to use Windows many years later.

ASCII windows may not have been everyone's cup of tea but I loved it.
by bjackman | 2026-03-12 22:30:29+00:00
In my case it's been a strong no. Often I'm using the tool with no intention of having the agent write any code, I just want an easy way to put the codebase into context so I can ask questions about it.

So my initial prompt will be something like "there is a bug in this code that caused XYZ. I am trying to form hypothesis about the root cause. Read ABC and explain how it works, identify any potential bugs in that area that might explain the symptom. DO NOT WRITE ANY CODE. Your job is to READ CODE and FORM HYPOTHESES, your job is NOT TO FIX THE BUG."

Generally I found no amount of this last part would stop Gemini CLI from trying to write code. Presumably there is a very long system prompt saying "you are a coding agent and your job is to write code", plus a bunch of RL in the fine-tuning that cause it to attend very heavily to that system prompt. So my "do not write any code" is just a tiny drop in the ocean.

Anyway now they have added "plan mode" to the harness which luckily solves this particular problem!