MurphyA/hacker-news huggingface dataset:
by timonoko | 2026-03-12 10:28:13+00:00
Gemini parsed 5000 lines assembly program. And it understood everything.

I wanted to change it from 32-bit MSDOS to 64-bit Linux. But it realized that the segmented memory model cannot be implemented in large memory without massive changes which breaks everything else.

It was willing to construct new program with seemingly same functionality, but the assembly code was so incomprehensible that whole project was useless as a learning tool. And C-version would have been faster already.

Sorry to say, but less talented humans like me-myself are already totally useless in this.
Show HN: Talk to a coding agent directly inside Zsh
by amitksingh1490 | 2026-03-12 10:28:20+00:00
Hi HN,

We built *ForgeCode*, a coding agent that integrates directly into *Zsh*.

After installing the plugin you can talk to it from your shell using `:` commands.

Example:

```
: add caching to this GraphQL resolver
```

Because it runs inside Zsh, your *aliases, plugins, and shell workflows keep working*.

Forge also appears *multiple times near the top of the Terminal-Bench 2.0 leaderboard* depending on the model configuration.

https://www.tbench.ai/leaderboard/terminal-bench/2.0

Project:
website: https://forgecode.dev
Repo: https://github.com/antinomyhq/forge

Curious if others have tried putting AI directly into the shell instead of using another CLI tool.
by cbeach | 2026-03-12 10:28:27+00:00
This is a fair argument but it’s rapidly becoming a non-argument.

LLMs have come a long way since ChatGPT 4.

The idea that they’ll always value quick answers, and always be prone to hallucination seems short-sighted, given how much the technology has advanced.

I’ve seen Claude do iterative problem solving, spot bad architectural patterns in human written code, and solve very complex challenges across multiple services.

All of this capability emerging from a company (Anthropic) that’s just five years old. Imagine what Claude will be capable of in 2030.
by jpfromlondon | 2026-03-12 10:28:34+00:00
It's much deeper than that probably because the kludge of english is in large part french.

But I also completely disagree, I don't think americans are attempting to pronounce croissant correctly for example, whereas brits will be much closer with no attempt at intentional mispronunciation, it just happens that brits are much closer on some and further on others, and vice versa re americans.

and I don't think there is any malice, in fact it became common among the british aspirational middle-class in the 70s to adopt french words in an attempt to appear cultured and upper, ironically now a clear marker of non-u.
by stavros | 2026-03-12 10:29:45+00:00
Eh, history has shown me that that's incorrect, though. In my culture, we're direct and just say what we want to say, whereas in US culture you have to be very circumspect or you get a bunch of downvotes. I've used an LLM to give me feedback so I can "anglicize" my comments, otherwise I get downvoted to hell.

Even in this comment, I initially wrote the start as "you're wrong", but then had to catch myself and go back and soften it to "that's incorrect", even though the meaning is the exact same. The constant impedance mismatch is tiring.
by Lucasoato | 2026-03-12 10:30:07+00:00
This is a consequence of introducing LLMs in software development. If you imagine it as a pyramid that starts from the bottom, the easiest tasks that happen more frequently, to the top, the hardest challenges that happen once in a while, LLMs can definitely help in automating the base of such pyramid, leaving the human with an harder job to do because now he statistically encounters harder tasks more often.

If this is the price to pay to unlock this productivity boost, so be it but let’s keep in mind that:

- we need to be more careful not to burnout since our job became de facto harder (if done at the maximum potential);

- we always need to control and have a way to verify what LLMs are doing on the easiest tasks, because even if rarely, they can fail even there (...but we had to do this anyway with Junior devs, or didn’t you?)
by sReinwald | 2026-03-12 10:30:10+00:00
> Overall this was a worthwhile assist. I believe (totally understandable) anti-AI animus is coloring a lot of these replies.

That, and hindsight bias. People know the second version came from an LLM, so it's automatically "flat." But if that edited comment had just been posted, nobody would've blinked. It reads fine.

IMO, there's a distinction worth drawing here: "AI edited" and "AI generated" are not the same thing. If you write something to express your own thinking, then use an LLM to tighten the phrasing or catch grammar issues, that's just editing. You're still the one with the ideas and the intent. The LLM is a tool, not an author.

The real failure mode is obvious enough: people who dump raw model prose into threads without critical review. The only one who "delved into things" was the model - not the human pressing send. That does flatten everything. But that’s a different case from a non-native speaker using a tool to express their own point more clearly.

The "preserve your voice" argument also smuggles in a premise I don't necessarily share - that everyone should care about preserving their voice. I'm neurodivergent. Being misunderstood when I know I've been clear is one of the most frustrating experiences there is. For some of us, being understood sometimes matters more than sounding like ourselves.
by felix9527 | 2026-03-12 10:30:54+00:00
The core problem this article surfaces is forensic: once the agent session ends, the evidence is whatever the vendor chose to log. Terminal scrollback is lossy, session logs are vendor-controlled, and "undo" only works if you catch it in time.

Certificate Transparency (RFC 6962) solved a structurally identical problem for TLS certificates after the DigiNotar incident. The insight: commit every action to an append-only Merkle tree where any third party can verify inclusion proofs — without trusting the log operator.

Applied to agents:
- Inclusion proof: "this specific action was recorded at position N, and the log hasn't been rewritten"
- Consistency proof: "between checkpoint A and B, the log only grew — nothing was removed or altered"

This gives you verification-based accountability, not trust-based logging. The difference matters: a signed receipt proves the signer said something happened. A Merkle inclusion proof proves it's part of a complete, append-only sequence — deletions are structurally detectable.

The AI agent ecosystem is having its DigiNotar moment weekly. We have the cryptographic tools to fix it. The question is whether we'll wait for a catastrophic incident to force adoption, like we did with CT.
by prohobo | 2026-03-12 10:31:02+00:00
Seeing a lot of "ok boomer" reactions to posts like this, and honestly I think I kind of agree - but more accurately the author hasn't considered the current landscape properly.

Grady Booch (co-creator of UML) has this to say about AI: this is a shift of the abstraction of software engineering up a level. It's very similar to when we moved from programming in assembly to structured languages, which abstracted away the machine. Now we're abstracting away the code itself.

That means specs and architectural understanding are now the locus of work - which is exactly what Neil is claiming to be trying to preserve. I mean, yeah you can give that up to the AI as well but then you just get vibecoded garbage with huge security/functionality holes.
Ask HN: Should training bottleneck detection be a product or just a feature?
by traceopt-ai | 2026-03-12 10:31:06+00:00
Hi,

I am building TraceML (open-source) focused on one practical outcome:

Automatically identify why a PyTorch training run is slow and suggest what to change.

Instead of raw traces or yet another dashboard, the goal is:

- highlight the top bottleneck(s) (data stalls, GPU waiting, comm/sync, memory/alloc issues)

- keep it lightweight enough to run regularly, not only during deep debugging

I would love honest feedback from people who run real training workloads:

Would you use something like this, or does it inevitably become another dashboard to maintain?

What would make it clearly useful vs noise?

Repo: https://github.com/traceopt-ai/traceml

Happy to clarify anything.
by yunseo47 | 2026-03-12 10:31:07+00:00
I agree with the direction, but it seems to miss the golden hour.
This concept should have been on the roadmap at least several years ago. After all, in most use cases, execution speed is not the main issue with JavaScript.

I believe that the need for JavaScript glue code has significantly hindered the appeal and interest in WASM, as well as the resulting ecosystem growth.
by PoignardAzur | 2026-03-12 10:31:23+00:00
So you double-count, you checksum (our table just tallied 100 ballots, do our vote counts sum to 100? good, keep going), you checksum some more (does our total vote count amount to the number of registered votes in this poll station), you film everything, and ideally you do this with volunteers drafted on election day.

This isn't rocket science.
by adamddev1 | 2026-03-12 10:31:23+00:00
> By the time you’ve sorted out a complicated idea into little steps that even a stupid machine can deal with, you’ve certainly learned something about it yourself.

I love these quotes. I got a much deeper, more elegant understanding of the grammar of a human language as I wrote a phrase generator and parser for it. Writing and refactoring it gave me an understanding of how the grammar works. (And LLMs still confidently fail at really basic tasks I ask them for in this language.)
by trhway | 2026-03-12 10:31:25+00:00
> The Iranian goal is very clear: they don't want to sign an agreement and be attacked again in three months or one year.

Yes, of course they want to continue to do what they've been doing and not be attacked for that. Yet it is just not possible. Iran's current regime overall main goal is the spread of Islamic Revolution. Hezbollah, Hamas, Houthis - these are typical metastasis of that spread. Terrorist acts, highly visible ones, is one of the effective tools of such a spread, and that way the terrorist acts are rational in the minds of Iran's regime and their above mentioned metastatic followers. There is no security framework possible which would still allow such a spread.
by das_keyboard | 2026-03-12 10:31:31+00:00
> I do miss coding, but it just isn't worth it anymore.

This pretty much sums up my current mood with AI. I also like to think, but it just isn't worth it anymore as a SE at bigCorp. Just ask AI to do it and think for you and the result only has to be "good enough" (=> works, passes tests). Makes sense business wise, but it breaks me, personally.
by scott_w | 2026-03-12 10:31:41+00:00
> Which manifesto commitments have been blocked in this parliament?

To be clear, I didn't say they "blocked," I said:

> though the Lords recently have been playing silly buggers around the Employment Rights Act

This was a manifesto commitment which, while it eventually went through, it was touch and go for a little bit. Reporting at the time:

https://www.youtube.com/watch?v=f412kJChC6g
by vindarel | 2026-03-12 10:31:43+00:00
Examples with screenshots: http://lisp-screenshots.org/

Some companies: https://github.com/azzamsa/awesome-lisp-companies/ (Routific, Google's ITA Software, SISCOG running resource planning in transportation, trading, big data analysis, cloud-to-cloud services, open-source tools (pgloader, re-written from Python), games (Kandria, on Steam and GOG, runs on the Switch), music composition software and apps…

More success stories: https://www.lispworks.com/success-stories/

I myself run web-apps and scripts for clients. Didn't ditch Django yet but working on that.
by afandian | 2026-03-12 10:32:49+00:00
The original solution involved a very thick disc which could then leveled and re-pitted. The problem was that the change in mass over time made it hard to calibrate the acceleration.

It also put a high radial load on the spindle whilst mounted sideways which led to run-out.

And flooding the area with radon (a heavy gas) helped the disc to float a bit, but had unexpected consequences...
by ninjagoo | 2026-03-12 10:33:15+00:00
> Good news then, you're currently on a forum! So we all agree that humans > AI

I made the post to specifically disagree with that notion: I think that excluding top-quality AI output from the discussion will reduce the overall quality of forums, because it's now the case that top-tier LLMs > average human.

How do we assess top-quality output? The moderation tools for that already exist. Doesn't scale well? I'm guessing the days where ai can do it cheaper and faster will soon be nigh.
Show HN: I built Chronoscope, because Google Maps won't let you visit 3400 BCE
by tinkeringtechie | 2026-03-12 10:33:32+00:00
I built Chronoscope, a project to explore the world through time.

I've been wanting to do this for a while, after being inspired by Ollie Bye's "History of the World" video several years ago.

I'm not the first person to have done this - resources like OpenHistoricalMaps are amazing.

But, I noticed there were a few disparate datasets / academic databases online, so I combined them together as best as I could (I've linked all sources in the app). To make it more interesting, I also included:

- Notable events from the time period (geolocated where possible), sourced from wikidata

- Ancient cities + their original names

- Empire hierarchies for colonial empires like the British Empire

You can jump across time and use shuffle to explore some fascinating corners of history.

Would love any feedback, especially from people who like maps, timelines, and weird historical rabbit holes. Also please report any data issues if you find them (it's all using publicly collated data, so there will be plenty).

Happy to publish code / data on GH if there's interest!
by quantiota | 2026-03-12 10:33:43+00:00
Most traders do not use raw tick data.
Here is a real-time chart showing how SKA handles price collisions and produces stable regime transition probabilities.

The alpha: price follows paired regime transitions.
A complete cycle of neutral → bull followed by bull → neutral drives the price up.
A complete cycle of neutral → bear followed by bear → neutral drives the price down.

The signal is not persistent states (bull → bull, bear → bear), but paired transitions.

Built with QuestDB 9.3.3 + Grafana + SKA real-time engine.
by f311a | 2026-03-12 10:34:00+00:00
> I still understand how everything works,

That's partly an illusion. Try doing everything manually. After only using inline suggestions for six months a few years ago, I've noticed that my skills have gotten way worse. I became way slower. You have to constantly exercise your brain.

This reminds me of people who watch tens of video courses about programming, but can't code anything when it comes to a real job. They have an illusion of understanding how to code.

For AI companies, that's a good thing. People's skills can atrophy to the point that they can't code without LLMs.

I would suggest practicing it from time to time. It helps with code review and keeping the codebase at a decent level. We just can't afford to vibecode important software.

LLMs produce average code, and when you see it all day long, you get used to it. After getting used to it, you start to merge bad code because suddenly it looks good to you.
by iso1631 | 2026-03-12 10:34:04+00:00
People have complained about things getting worse literally for millennia

Either 2000 years ago life was great, or people saying "things were better" tend to be wrong

https://historyhustle.com/2500-years-of-people-complaining-a...

Things are different, people want different things today then they did in the 80s. The top lego sets of the 80s were bought by rich parents for their kids. Adults didn't buy lego for themselves.

Today they're bought by rich adults for themselves, who want different things

Meanwhile kids aren't as bored. In the early 90s as a 10 year old I used to watch soap operas with my parents, because there wasn't much more to do at 8pm on a wet december evening. That was evidenced by Coronation street getting 17 million viewers, well over 1 in 4 people in the country.

Today the same program gets 2 million viewers, nearer to 1 in 40.

That's not because it's materially worse, but because there's more things to do.

Lego has the same issue. In the 80s as a kid there was little to do at home, so things like lego, meccano, spirograph took up the time. Today there's a lot more to do.

There's a reason 80s lego sets aren't as popular as they were in the 80s - the actual sets - and it's clearly not the quality (as a lego 80s set is the same today as it was 40 years ago).
by AngryData | 2026-03-12 10:34:07+00:00
I don't know if I agree with their conclusion on #3, beef is fed 90% alfalfa grass which is literally cheaper than dirt and fixates its own nitrogen. Yeah they eat more feed per pound of meat, but alfalfa is literally the cheapest and easiest crop to grow. Sow it, mow it, bail it, now you have good ground to plant grains in without artificial fertilizer next year. You only feed cows grains during their last month to finish them to increase marbling/fat content.

If you produce less beef, you grow less alfalfa, and you end up using more artificial fertilizer which might even raise grain prices.
by hrmtst93837 | 2026-03-12 10:34:22+00:00
Git-based systems sound clever until you hit the delights of merge conflicts and history rewrites from trolling or spam. Propagating edits or deletes in a decentralized social network via git is a full-time job for bots unless you limit activity to a few dozen people who never disagree. Static sites dodge a lot of cross-user sync pain at the cost of making anything dynamic feel like pulling teeth with chopsticks.
by newswasboring | 2026-03-12 10:34:45+00:00
I have a stupid solution for this which is working wonders. It does not help to tell the LLM "don't do this pattern". I literally make it write a regex based test which looks for that pattern and fails the test.

For example I am developing a game using GDscript, LLMs (including codex and claude) keep making scripts with no classnames and then loading them with @preload. Hate this, and its explicitly mentioned in my godot-development skill. What agents can't stand is a failing test. Feels a bit like enforcing rules automatically.

This is a stupid idea but it works wonders on giving taste to my LLM. I wonder if I should open source that test suite for other agentic developers.
by manfre | 2026-03-12 10:35:07+00:00
Any take home test trivial enough to complete in under 20 minutes could be completed by an AI. The only signal you get from a take home test is whether or not they can submit answers. It doesn't let you know if the candidate is capable of passing the test unassisted.

Take home tests were never a worthwhile signal. Pre-AI, people would search for solutions or have another person complete it.
by pjmlp | 2026-03-12 10:35:38+00:00
Yes, people do build anything with Lisp, that is why there are at least two commercial Common Lisp systems around, LispWorks and Allegro Common Lisp.

Google Flights is an acquisition of a company using Lisp, ITA Software, they even have a Lisp guide.

https://google.github.io/styleguide/lispguide.xml

In Portugal, Siscog used to be a Lisp shop, no idea nowadays.

Then you have the Clojure based companies, where Datomic and Nubank are two well known ones, even if not a proper Lisp, still belongs to the same linage.
by roryirvine | 2026-03-12 10:35:41+00:00
The parliament of Northern Ireland also used STV for the same (er, well, inverted) reasons from 1921 until the Unionist majority forced a change to FPTP for most seats in 1929.

More generally, STV was the default choice for assemblies throughout the British Empire (and became known as 'the British system' as a result) from the late 19th century onwards.

It was even agreed on for use in Westminster in 1919 - though only the university seats ever actually used it - making it "more traditional" than the current single-member FPTP system which dates only from 1949. The failure to actually implement it was part of a more general reactionary movement in the aftermath of the war, when Lloyd George's promise of a "land fit for heroes" was thoroughly betrayed.

The Irish system seems to work well, and can be used as a comparator for considering what the UK might look like if that betrayal hadn't happened.
by shaunpud | 2026-03-12 10:36:15+00:00
Does your project use changedetection.io behind the scenes? When I look at the _All Watches Feed_ the contents of the rss file include;

<?xml version='1.0' encoding='UTF-8'?>
<rss xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/" version="2.0"><channel><title></title><link>https://changedetection.io</link><description>Feed description</description><docs>http://www.rssboard.org/rss-specification</docs><generator>python-feedgen</generator><lastBuildDate>Thu, 12 Mar 2026 10:10:10 +0000</lastBuildDate></channel></rss>
by bayindirh | 2026-03-12 10:36:27+00:00
This is quite an interesting question, because I believe there's two facets to the surface of the question.

Given you're interacting with a competent hacker (i.e. a person who is into tech not for money and for tinkering), you can't impress them. You can pique their interest, they may praise you, but if they are informed enough, anything looking like magic can be dissected easily. So technical excellence is meaningless.

Given you're interacting with a competent hacker again, everything technical will be subjective. Creating is deciding trade-offs all the way down and beyond. Their preferences will probably lay at a difference balance of trade-offs. Even though you catch "objective" perfection, even this perfection has nuances (see USB audio interfaces. They all have flat response curves, but they all sound different, for example), hence, technical excellence is not only meaningless, it's subjective.

On a deeper level, a genuine person who knows its cookies well, even though with gaps is a much more interesting and nicer person to interact with. They'll be genuinely interested in talking with you, and learn something from you, or show what they know gently, so both parties can grow together. They might not be knowledgeable in most intricate details, but they are genuinely human and open to improvement and into the conversation itself, not to prove themselves and win a meaningless battle to stroke their own ego.

An LLM generated response is similar. It's lazy, it's impersonated, it's like low quality canned food. A new user recently has written an LLM generated rebuttal to one of my comments. It's white-labeled gibberish, insincere word-skirmish. It's so off-putting that I don't see the point to reply them. They'll just paste it to a non-descript box and will add "write a rebuttal reply, press this point". This is not a discussion, this is a meaningless fight for internet points.

I prefer genuine opinions, imperfect replies, vulnerable humans at the other end of the wire. Not a box of numbers spitting out grammatically correct yet empty sentences.