MurphyA/hacker-news huggingface dataset:
by kypro | 2026-03-08 20:00:18+00:00
Technology didn't replace agricultural workers either, but you'd think it did when you consider how few people work in agriculture as a share of the population today.

By providing productivity tools you do effectively replace jobs because there's only so much of a good or service a person will want to consume.

For example, just because a game dev studios can make 10x more games with AI, this doesn't mean the industry will make 10x more money unless demand for video games increases. Instead what is likely to happen as the cost of making games reduces is that the price of games for consumers will drop too as competition increases, which will turn hurt game dev profits, so game dev studios will likely have to be 10x smaller in the future – even if there's still technically people working in the industry.

However when the work of agricultural workers became increasingly automated there were lots of other industries people could work instead, at the time that was factory work, and although the details will be different, I'm sure to some extent this will happen with white collar work too. But the question I'd ask today is what is that alternative source work, and is it as good as white collar work?

Our economy went from, farming -> factory work -> office work. I strongly suspect the next step will be more people working in manual labour jobs and working in servant type roles. It's hard to see where else the demand will come from.
by ninalanyon | 2026-03-08 20:00:26+00:00
Of the seventeen countries (including China, Saudi, Thailand, USA, etc.) I have visited over the last four decades the only time I have been taken out of the queue at passport control to be interviewed was at Toronto flying in from Europe. Actually the tone of voice was more suited to interrogation than polite inquiry. It was very odd, and quite at odds with both my impression of and experience of Canadians themselves.
by jauntywundrkind | 2026-03-08 20:01:01+00:00
This is a not-so subtle advantage JavaScript has over 90% of everything else: Chrome DevTools Protocol (CDP), which exists/is-great in-large-part thanks to JavaScript being an alive language. Of the Stop Writing Dead Programs variety (https://jackrusher.com/strange-loop-2022/, https://news.ycombinator.com/item?id=33270235). It's just astoundingly capable, so very richly exposes such a featureful runtime, across so many dimensions of tooling. REPL, logging, performance, heap, profile, storage, tracing and others, just for the core, before you get into the browser based things. https://chromedevtools.github.io/devtools-protocol/

This is such a core advantage to javascript: that it is an alive language. The runtime makes it very easy to change and modify systems ongoingly, and as an operator, that is so so so much better than having a statically compiled binary, in terms of what is possible.

One of my favorite techniques is using SIGUSR1 to start the node debugger. Performance impact is not that bad. Pick a random container in prod, and... just debug it. Use logpoints instead of breakpoints, since you don't want to halt the world. Takes some scripting to SSH port forward to docker port forward to the container, but an LLM can crack that script out in no time.
https://nodejs.org/en/learn/getting-started/debugging#enable...

My cherry on top is to make sure the services my apps consume are attached to globalThis, so I can just hit my services directly from the running instance, in the repl. Without having to trap them being used here or there.
by alabhyajindal | 2026-03-08 20:01:25+00:00
100%. Not sure what the solution is but I have lost interest in Show HNs these days. Part of it is because when someone posted before, it usually meant they spent a fair amount of time thinking, and found it worthwhile to spend energy on the project. This was a nice first filter for bad ideas and now no longer exists.

Even for posts that are interesting to me, I get the feeling that it's not looking at because it was probably made using LLMs. Nothing against them, but I personally thought of Show HNs as doing something for the love of it, the end result being a bonus.
by est31 | 2026-03-08 20:01:26+00:00
You can't train LLMs on proprietary data, at least not if you want to make that LLM as accessible as Gemini. Otherwise random people can ask it your home address.

So it matters less than one would think. Also, ChatGPT can do 'internet search' as a tool already, so it already has access to say Google maps POI database of SMBs.

And ChatGPT also gets a lot of proprietary data of its own as well. People use it as a Google replacement.
by _DeadFred_ | 2026-03-08 20:01:26+00:00
The Industrial revolution wasn't painless. 1880-1947 had a huge amount of awfulness and chaos and suffering (and post 1947 recovery took DECADES for much of the world).

Lifespans in Manchester and London FELL compared to the countryside. Labor violence was intense involving Pinkertons and private security and death and violence.

Mechanization/railroads/new weapons allowed violence on a horrific level against native populations around the world. Those are all industrial revolution deaths.

During the great depression Americans wanting to work literally starved to death, 12.8% of maternal deaths were from septic abortion because woman had no access to doctors but couldn't afford a child. That was part of the 'transition' process.

There were 2 Industrial world wars enabling horrors never seen before. War so bad it took decades for nations to recover and ending in nuclear standoff the threatened to end the world in 15 minutes if there was one misunderstanding.

We pretend like the 1880s blacksmith became a 1950s American suburbanite when in fact they moved to shared housing in the city for poverty wages and a shorter lifespan, lost their fingers/arms in machines (because Industrial barons cared about safety as much as AI titans do) and ended up living on skid row, the section of town for failures who couldn't 'adapt' to the new modern industrial age world. Their children died in WW1 in a trench to industrial produced gas. Their children's children died storming a beach in WW2. And their children's children's children lived on meager 1940/1950 diets as the world rebuilt it's food stocks eating new industrial food replacements like margarine and SPAM (staples through the 1970s).

That all gets waived away with 'always worked to society's benefit'. It took almost 70s years and the destruction of the rest of the worlds economies/infrastructure to create that 1950s American suburbanite world. 'always worked to society's benefit over the long term' is just handwaving not based on the reality of people's lives and the 100-200 dead from Industrial warfare on the way to today.

And because we now talk in AI speak with a weird ass final AI sounding point...people/nations didn't even have a choice. Japan tried. But they were forced to 'modernize'. Once one nation passed through that door, every nation had to follow. Post industrial revolution those that didn't join in were all subjugated and hundreds of millions died horrible horrible deaths.
by lostlogin | 2026-03-08 20:01:41+00:00
> And having everything virtualized on a single box is a pretty easy and highly flexible way get going and experiment. Also if it's on a ZFS backing makes "reset/rollback world" quite straight forward with minimal understanding given you can just use the same snapshot mechanism for that as you do for all other data.

Docker-compose isn’t a backup, but from a fresh ubuntu server install, it’ll have me back in 20 mins. Backing up the entire VM isn’t too hard either.

I was in a really sweet spot and then ESXi became intolerable. Though in fairness their website was alway pure hell.
by GaryBluto | 2026-03-08 20:01:52+00:00
> human.json is a lightweight protocol for humans to assert authorship of their site content and vouch for the humanity of others. It uses URL ownership as identity, and trust propagates through a crawlable web of vouches between sites.

This will not (and shouldn't) be used by more than a handful of people who were likely already friends anyway. It's an odd fauxlution to a problem that is easily avoidable in the first place.
by ratsimihah | 2026-03-08 20:02:38+00:00
How long has it been? It can’t not be hard at first. But if you try hard enough you’ll learn to be comfortable with yourself and be alone. Finding hobbies does help for sure, particularly those that involve people.

You could try yoga too, starting from scratch is a great place to begin. It’s a great tool to learn to see yourself objectively and be able to let external things affect you less. (I’ve been practicing for 10ish years and teaching for 5ish) Also yoga communities are usually great because it’s mostly people trying to actively improve themselves. But do go for the dynamic style if you try it, because it builds the mind but also the body. So even if you don’t get into the spiritual stuff, you always get a good workout.

Best of luck. Hope you can find the strength to embrace the pain and not flee or hide from it, because it truly makes us stronger.
by heavyset_go | 2026-03-08 20:03:24+00:00
This made the frontpage two days ago: https://news.ycombinator.com/item?id=47275291

Read the comments and you'll see it took time and effort, from people who know at least a little about what they're saying, to point out that it's AI slop that doesn't live up to the claims written in its own docs.
by spopejoy | 2026-03-08 20:03:55+00:00
The jury is not out -- it's an unconfirmed hunch that, as the study you link notes, risks harming patients who are having trouble keeping down food as it is.

This is just keto and fasting fans pushing their obsession on cancer patients. Same for marijuanauts -- anti-nausea drugs have long outperformed cannibinoids but you still have stoner friends offering you spliffs (ok, save them for later)
by joefrost01 | 2026-03-08 20:03:58+00:00
The thing I’ve noticed with LLM-assisted development is that the language ecosystem matters far more than people expect.

Once a codebase gets beyond a few thousand lines, models stop struggling with syntax and start struggling with entropy. If the ecosystem allows many ways to structure the same program, the model’s output begins to drift.

I’ve tried building non-trivial projects with LLM assistance in Java, JavaScript, Python, Rust, C++ and Go. The difference in how well the models hold the system in their "head" becomes obvious once you pass a few thousand lines of code.

Python and TypeScript in particular have a massive combinatorial space: frameworks, build systems, typing styles, dependency patterns, project layouts. Two teams solving the same problem can produce codebases that look completely different. That variability leaks into the training distribution and the model has to guess which universe it’s operating in.

Go sits at the opposite end of that spectrum.

There is essentially:

- one formatting style

- one standard build system

- one dependency mechanism

- one dominant project layout

- a very small set of concurrency primitives

- a language that has barely changed in a decade

That constraint turns out to be exactly what LLMs thrive on. The solution space is narrow, so the model converges instead of wandering.

In my experiments, once a project passes ~8k lines most languages start to show cracks: incorrect imports, wrong framework idioms, subtle API hallucinations. With Go the agents stay coherent much longer. Extremely fast build times and batteries-included tooling also tighten the feedback loop significantly.

Java often gets suggested as an alternative because it’s statically typed and mature. But in practice the ecosystem is a maze: Maven vs Gradle, Spring everything, annotation magic, layers of frameworks, multiple architectural styles. The language may be stable, but the surrounding universe isn’t.

I’m also a big Rust fan. If you genuinely need Rust’s capabilities it’s an excellent tool. But it’s slower to compile and significantly more complex for LLMs to work with. Beyond small codebases the difference becomes noticeable.

One thing that helps regardless of language is architecture. Strong modular boundaries, API-only feature access, and good code maps make a huge difference when working with LLMs.

Used carefully, these tools are a huge productivity multiplier. The interesting question now isn’t whether LLM coding works - it’s which languages, practices, and system designs allow it to work reliably at scale.
by cadamsdotcom | 2026-03-08 20:04:29+00:00
People used to be programmers, but the ratio of typing to problem solving eventually caught up. Now programming is just part of the job.

Software engineering is falling to this trend too (somewhat)

The solution is to stop merely thinking of yourself as a software engineer and move up to the level of “manager of agents”.. but actually, managers deal with human stuff and this is fascinatingly mechanical - in fact even the unpredictability of these new tools is quite predictable. And so, a more useful framing is “software development process engineer”.

You can look at all the literature on building factories and production lines for ideas on what you’ll be doing.

You shouldn’t ever just have your agent write the software then review and ship it. You are missing massive opportunities to take yourself out of more loops over time. What self-reflection are you and the model doing to catch opportunities to improve? What is your method for codifying your acceptance criteria, so your agents can do the work to higher quality over time without you in the loop to get it there? What’s your process for continuous improvement? How do your models know what work other team members’ models are doing simultaneously so there’s less stepping on toes? Can THAT be automated so you don’t need to sit in Slack and trade “human-verbal locks” on areas of the architecture?

There’s immense room for creativity in the role of a software development process engineer.
by sublinear | 2026-03-08 20:04:29+00:00
> This is especially important if the primary role of engineers is shifting from writing to reading.

This was always the primary role. The only people who ever said it was about writing just wanted an easy sales pitch aimed at everyone else.

Literate programming failed to take off because with that much prose it inevitably misrepresents the actual code. Most normal comments are bad enough.

It's hard to maintain any writing that doesn't actually change the result. You can't "test" comments. The author doesn't even need to know why the code works to write comments that are convincing at first glance. If we want to read lies influenced by office politics, we already have the rest of the docs.
by andai | 2026-03-08 20:04:57+00:00
Yeah it's weird, there was one case where I thought it was AI but wasn't sure. Several other comments pointed it out, too. Author claimed he wrote it manually. (Which is honestly even more concerning!)

Maybe there can be a dedicated 'flag botspam' button?

Then again it's a nuanced issue. I see AI used in a large percentage of writing now, so would this rule apply to the article as well?
by stratos123 | 2026-03-08 20:05:10+00:00
Personally I'm not even sold on the current paradigm being too limited to produce AGI - there are still several OOMs worth of compute increase available, plus the algorithmic improvements have overall been accumulating faster than predicted.

But even assuming that a major breakthrough is required, it seems ludicrous to me to go from that to a timeline of a decade or more. This isn't like fusion power research, where you spend 10 years building a new installation only to find new problems. Software development is inherently faster, and AI research in particular has been moving extremely quickly in the past. (GPT-3 is only 6 years old.) I don't think a wall in AI progress, if one comes at all, will last more than a few years.
by furyofantares | 2026-03-08 20:05:12+00:00
I was paying both $200+/mo and I went down to only paying Anthropic $200/mo.

My experience has, for a few months, been that OpenAI's models are consistently quite noticeably better for me, and so my Codex CLI usage had been probably 5x as much as my Claude Code usage. So it's a major bummer to have cancelled, but I don't have it in me to keep giving them money.

I'd love to get off Anthropic too, despite the admirable stance they took, the whole deal made me extra uncomfortable that they were ever a defense contractor (war contractor?) to begin with.
by mmooss | 2026-03-08 20:05:12+00:00
[2025]

J.R.R. Tolkien, both the leading practitioner of fantasy and a leading scholar of Old English (Anglo-Saxon) and related languages and, at least adjacently, their 'fantasy' myths and stories, argued that the focus of fantasy is not character or plot nor even the protagonist, but the fantasy world and the reader's (vicarious) exploration of it.

I wonder how the high-level LARP designers, and players, would respond to that. They clearly put a lot into creating their world and making it compelling, and we might argue that the point of LARP is to give audience a more direct experience of the world than reading or watching or playing on a computer. The article talks mostly of emotional experience (which doesn't exclude the world and its exploration) and plot.
by xorvoid | 2026-03-08 20:05:12+00:00
There's already some good advice in this thread, but I want to add more.

This will indeed be very hard, but I'd urge you to take a long-term and positive forward looking approach.

It sounds to me like you don't have the best family/friends social structure to depend on. I'd focus on building that. It will take time ... and it won't happen on your schedule. The cold hard fact is that you have to put yourself out in the world in social spaces and be open and vulnerable. This is often why shared hobbies are recommended. But the hobbies aren't entirely the point. The point is that you're engaging in the real world with real people and learning to be open and vulnerable in that environment. If you embrace that (truly embrace), the friends and relationships will eventually come. But, it may take a long time. It's a long game. But its worth it.

In the short-term, you can find ways to cope. For me, I got REALLY deep into ultra-running after a bad breakup. It helped. But, it was seriously just a cope for not having the foundational social structures that everyone needs.

In summary: find healthy short/medium term coping methods, and invest in building longer-term social connections. And expect it to take some time. Give yourself grace. You're doing a hard thing. It's okay for it to be a struggle. Just keep working on it and you'll get through it. I've been through this. It gets better, I promise!

Good luck. I'm rooting for you!
by drzaiusx11 | 2026-03-08 20:05:19+00:00
There's a number of "immortal" human cell lines dating back to as far as the 1950s (you may have heard of Henrietta Lacks? [1] and the immortal HeLa cell line).

Today there are several
immortalized neuron cell lines used in research to model neuronal function, like HeLa but of neuron type obviously, that are also typically derived from tumours (e.g., SH-SY5Y, PC12) or immortalized via genetic modification (e.g., v-myc) like CTX0E03 [2] which was designed to allow for continuous growth in the presence of particular reagents.

1. https://en.wikipedia.org/wiki/Henrietta_Lacks

2. https://www.prnewswire.com/news-releases/reneuron-announces-...
by dnautics | 2026-03-08 20:05:41+00:00
I'm not 100% convinced that "plugging memory error holes" was right at the compiler level.

Currently building out clr, which uses a heuristic (not formal verification) method for checking soundness of zig code, using ~"refinement types". In principle one could build a more formal version of what I'm doing.

https://github.com/ityonemo/clr
by sam_palus | 2026-03-08 20:05:53+00:00
I'd totally agree, if it took 1-2 weeks to onboard and manage! But it really does just take a few minutes.

And it'll get even easier once we add our auto-sweep features in the next few weeks, and you'll be able to just set it up once and truly never have to touch it again.

We certainly don't claim that Palus will transform your startup. But it's a worthwhile piece of very low-hanging fruit.
by thatfrenchguy | 2026-03-08 20:06:31+00:00
I had to go look at my Costco and Amazon orders to check because my intuition was that I spent so much more money in diapers in the first year and indeed, that was like ~75% of the cost of the first two years. Toddlers get changed so much less often than babies, and you can plan your purchases way more easily, so I’m not even sure they make that much money off those.
by opan | 2026-03-08 20:06:55+00:00
Nitpick, but I love vim (and to a lesser extent emacs) and am not a programmer (sadly). I don't believe you need to be a programmer to use them. Using vim is "just" using your computer. Personal notes, system configuration (dotfiles), anime playlist management (.m3u files mainly), checking the name of a unicode character I don't recognize (vim-characterize), inverting capitalization (select and hit ~) or making large formatting changes to some text (block select visual mode and multi-line editing, macros) to post elsewhere, bulk renaming of files (vidir), writing emails (aerc), vim is my go-to for all that. That's not even getting into vim-inspired separate programs like ranger and qutebrowser.
by xvector | 2026-03-08 20:07:41+00:00
> It's them killing islamic terrorists trying to commit genocide on people celebrating at a Christmas parade.

You are woefully unfamiliar with the state of AI today.

Top models frequently fail to write working code, often provide nonsensical suggestions like "walking your car to the carwash 50 meters away," and you think they can accurately identify whether someone is a terrorist or not?

Yesterday Opus 4.6 couldn't solve a simple geometry problem for me (placing a dining set on a balcony), you think it's ready to kill people without human in the loop?

Look - no one is disagreeing that terrorists need to be killed. We all want that. But the models we have today are not ready to do so autonomously without incurring civilian casualties.

> It's the fact they refuse to let them research or do those things.

Actually, no, Anthropic has zero problem with the government researching this and even offered to help make this a reality. It's in their memo and in Dario's interview.

> There's safeguards,

Like what? More unreliable autonomous systems?

> Just because you don't like the president

I don't mind Trump, please stop putting words in my mouth.
by diarrhea | 2026-03-08 20:07:43+00:00
Agree. I am note sure I understand the premise of the article. You're now recording encountered errors twice, which can look like

cancel(fmt.Errorf(
"order %s: payment failed: %w", orderID, err,
))
return fmt.Errorf("order %s: payment failed: %w, orderID, err)

Not only that, isn't this a "lie"? You're cancelling the context explicitly, but that's not necessary is it? Because at the moment the above call fails, the called-into functions might not have cancelled the context. There might be cleanup running later on which will then refuse to run on this eagerly cancelled context. There is no need to cancel this eagerly.

Perhaps I'm not seeing the problem being solved, but bog-standard `return err` with "lazy" context cancellation (in a top-level `defer cancel()`), or eager (in a leaf I/O goroutine) seems to carry similar functionality. Stacking both with ~identical information seems redundant.