MurphyA/hacker-news huggingface dataset:
by kuerbel | 2026-02-07 18:14:02+00:00
You're mixing up refugees and economic migrants, which makes the argument collapse immediately.

Refugees are not "imported." They are people fleeing war, persecution, or state collapse under international law obligations that Europe helped write. You don't get to say "we'll take the engineers, but not the bombed-out schoolteachers." Treating asylum like a points-based talent visa is a category error, not a policy preference.

The brain drain argument absolutely does hold water. Systematically pulling scarce doctors, engineers, and academics out of low-income or fragile states weakens those societies. Some people return and contribute, yes, but many don't, and many return to systems too damaged to absorb their skills. That's not controversial. It's well documented in development economics.

What's being presented as "common sense" here is really a value judgement: that human worth should be ranked by immediate economic utility to the receiving country. That's not a fact, and it's not how real migration systems actually work.

If the goal is serious policy discussion, collapsing refugees, migrants, education, and prosperity into a single slogan doesn't get you there. It just makes the world simpler than it is.

One more point about the word "import," because language matters in how we think about policy.

Describing people as being "imported" frames migration as a centrally planned, top-down process, rather than as a response to war, persecution, economic collapse, or climate pressure. It shifts attention away from those underlying causes and toward the idea that governments are deliberately "bringing people in" as if they were interchangeable inputs.

That framing makes it easier to talk about migrants in abstract, instrumental terms, sorted by usefulness rather than understood as people reacting to circumstances, and it tends to oversimplify how migration actually works in practice, which is far more reactive and constrained than intentional or engineered.

Being precise about language helps keep the discussion grounded in reality rather than drifting into metaphors that flatten complex human movement into something it isn't.
by delecti | 2026-02-07 18:14:40+00:00
Scroll further down (specifically to the section titled "Wait, $1,000/day per engineer?"). The quote in the quoted article (so from the original source in factory.strongdm.ai) could potentially be read either way, but Simon Willison (the direct link) absolutely is interpreting it as $1000/dev/day. I also think $1000/dev/day is the intended meaning in the strongdm article.
Ask HN: Will LLMs/AI Decrease Human Intelligence and Make Expertise a Commodity?
by mc-0 | 2026-02-07 18:15:09+00:00
I'm almost 4 years into my career as a software engineer. Before widespread LLM adoption I had to do a lot of research when writing code.

When replacing SWEs in the future gets discussed, a lot of people say things like "Oh someone has to review the code" and "they'll always need to be a human in the mix". But when are these humans supposed to acquire this knowledge?

Claude Code can help me create things a lot faster. I can vibe code stuff that would take me a lot of time to learn and build. But I understand none of it. When people talk about productivity, it seems like most gloss over the fact that those who already know how to do things & have experience are going to be the most productive. Yet I often hear no discussion as to how people should be bridging the knowledge gap.

I am sure others make a deliberate effort to learn while they leverage these tools, but human beings are lazy. With the constant pressure to increase velocity & productivity at all costs, people aren't going to prioritize learning things. At work I already see SWEs & people in technical roles taking the path of resistance:

- Asking copilot in agent mode to run a command instead of literally typing it themselves

- Suggesting a mermaid diagram for a large legacy system written in COBOL is accurate because "that's what the LLM said"

- Making the statement that "we really won't need to understand data structures & algorithms in the future, those problems are already solved"

Doesn't it seem like the era of AI is devaluing knowledge or talent and dressing it up as though it's making people more productive in ways they otherwise wouldn't be?
by squidbeak | 2026-02-07 18:15:22+00:00
I agree. We've been assured by these skeptics that models are stochastic parrots, that progress in developing them was stalling, and that skills parity with senior developers was impossible - as well as having to listen to a type of self-indulgent daydreaming relish about the eventual catastrophes companies adopting them would face. And perhaps eventually these skeptics will turn out to be right. Who knows at this stage. But at this stage, what we're seeing is just the opposite: significant progress in model development last year, patterns for use being explored by almost every development team without widespread calamity and the first well-functioning automated workflows appearing for replacing entire teams. At this stage, I'd bet on the skeptics being the camp to eventually be forced to make the hard adjustments.
by data_maan | 2026-02-07 18:15:30+00:00
Very serious for mathematicians - not for ML researchers.

If the paper would not have had the AI spin, would those 10 questions still have been interesting?

It seems to me that we have here a paper that is solely interesting because of the AI spin -- while at the same time this AI spin is really poorly executed from the point of AI research, where this should be a blog post at most, not an arXiv preprint.
by raw_anon_1111 | 2026-02-07 18:15:40+00:00
It’s a red flag anytime I see a company with a dedicated “database administrator” usually they want you to put all of your business logic in stored procedures and have a dozen GetCustomer_n copies for versioning.

What can a modern operations person do that can automated anything via coding?

BTW: I am “expert” in cloud by any definition (did at a startup, worked at AWS ProServe, staff consultant at a 3rd party consulting company) and I develop. How hard do you really think it is for someone with a developer mindset to learn how system design works at scale and bring their same developer mindset to infrastructure as code?

It took me exactly 2.5 years from opening the AWS console for the first time to being hired at AWS.

Everyone in my division at my current company at my level can hold their own as either a developer or a “senior cloud engineer”. We just find infrastructure babysitting incredibly boring

Half the reason I learned cloud was not because I didn’t want to manage servers - I didn’t want to deal with server administrations.
by mejutoco | 2026-02-07 18:15:41+00:00
Original claim was:

> At that point, outside of FAANG and their salaries, you are spending more on AI than you are on your humans

You say

> Assuming 20 working days a month: that's 20k x 12 == 240k a year. So about a fresh grad's TC at FANG.

So you both are in agreement on that part at least.
by anarticle | 2026-02-07 18:15:53+00:00
Since we're on door handle memory lane, I was a huge fan of used Volvos when I was in my 20s, had a 740 and an 850. I loved the trigger 740 handle and the 850s whole handle pull. I'm sure they were complex and expensive to replace, but if it's made right the first time you won't have to. I had over 200k on the Volvo before I sold it which it felt like the same car I bought 6y ago.
by rck | 2026-02-07 18:16:22+00:00
It's interesting that the main thinkers listed are all Roman. They're definitely the best known, but Stoicism was a Greek philosophy first and foremost, and Cleanthes, Chrysippus, etc. were more significant than any of the Romans.

Stoicism had a lot going for it, but it was also full of a lot of crazy nonsense - there's a reason you've never met a Stoic who was fully on board with Stoic natural philosophy or "physics." The logic eventually made a comeback (via Frege, possibly due to plagiarism!), and the virtue ethics got absorbed into Christian moral philosophy by about the 13th century (by way of neo-platonists who influenced Dominican philosopher theologians like Aquinas). It's not surprising that it ran out of steam.
by kaicianflone | 2026-02-07 18:16:59+00:00
I agree with this almost completely. The hard part isn’t generation anymore, it’s validation of intent vs outcome. Especially once decisions are high-stakes or irreversible, think pkg updates or large scale tx

What I’m working on (open source) is less about replacing human validation and more about scaling it: using multiple independent agents with explicit incentives and disagreement surfaced, instead of trusting a single model or a single reviewer.

Humans are still the final authority, but consensus, adversarial review, and traceable decision paths let you reserve human attention for the edge cases that actually matter, rather than reading code or outputs linearly.

Until we treat validation as a first-class system problem (not a vibe check on one model’s answer), most of this will stay in “cool demo” territory.
by jessmartin | 2026-02-07 18:17:29+00:00
I’ve been building using a similar approach[1] and my intuition is that humans will be needed at some points in the factory line for specific tasks that require expertise/taste/quality. Have you found that the be the case? Where do you find that humans should be involved in the process of maximal leverage?

To name one probable area of involvement: how do you specify what needs to be built?

[1] https://sociotechnica.org/notebook/software-factory/
by rune-dev | 2026-02-07 18:17:43+00:00
Right, I understand of course that AI usage and token costs are an investment (probably even a very good one!).

But my point is moreso that saying 1k a day is cheap is ridiculous. Even for a company that expects an ROI on that investment. There’s risks involved and as you said, diminishing returns on software output.

I find AI bros view of the economics of AI usage strange. It’s reasonable to me to say you think its a good investment, but to say it’s cheap is a whole different thing.
by bediger4000 | 2026-02-07 18:18:26+00:00
Oligarchs (A) are very irritated at classes of workers, or economic classes that have some independence and power, and (B) cannot wait until everyone other than they are assigned to neat little commodity pigeonholes.

The whole article seems to be founded upon this:

More than 60% said they would consider pivoting into a skilled trade if it offered more money and stability

That's not a shocking number. Of course workers want more money AND stability. The "stability" part is what keeps a lot of people out of the lucrative armed robbery sector, after all.
by noosphr | 2026-02-07 18:18:48+00:00
I was looking for some code, or a product they made, or anything really on their site.

The only github I could find is: https://github.com/strongdm/attractor

Building Attractor

Supply the following prompt to a modern coding agent
(Claude Code, Codex, OpenCode, Amp, Cursor, etc):

codeagent> Implement Attractor as described by
https://factory.strongdm.ai/

Canadian girlfriend coding is now a business model.

Edit:

I did find some code. Commit history has been squashed so you can't tell what was going on: https://github.com/strongdm/cxdb

There's a bunch more under the same org but it's years old.
by dataviz1000 | 2026-02-07 18:19:15+00:00
We live in a world of competition -- even in Soviet communism. As long as people can wrack their brain to get an edge, they will.

Likely the way calculators replaced calculators (people who sat in a room and calculated), AI will replace some jobs. Economics and history have shown that this tends to create more jobs of different sorts and than certain jobs that have been lost to automation.

There is no reason riot and burn Murdoch's printing presses to the ground.
by pragmatic | 2026-02-07 18:19:54+00:00
These are the blog posts we need.

This is the siren song of llm. "Look how much progress we made"

Effort increases as time to completion decreases. The last 10% of the project takes 90% of the effort as you try to finish up, deploy,integrate and find the gaps.

Llms are woefully incapable of that as that knowledge doesn't exist in a markdown file. It's in people's heads and you have to pry it out with a crowbar or as happens to so many projects, they get released and no one uses it.

See Google et Al. "We failed to find market fit on the 15th iteration of our chat app, we'll do better next time"
by jacquesm | 2026-02-07 18:20:20+00:00
> The installer, written in Python, often failed because of incorrect assumptions about the target environment and almost always required some manual intervention to complete successfully.

Nothing ever changes. I spent half a day just getting some SDR development stuff to work just now, long live Python code with baked in hard dependencies on particular versions of obscure libraries... In the end it worked, but what a mess.
by 1vuio0pswjnm7 | 2026-02-07 18:21:22+00:00
I have zero problems with the terseness of the k language, the names of the source files nor the source code they contain

I find brevity easier to work with. I wish all software was like that

I like the shell (ash not bash). I like assembly language

I have to "adjust" to verbosity, and sometimes I honestly can't, it's paralyzing to the brain, terseness feels more natural

Why not name scripts in natural language like an LLM prompt perhaps (I don't use LLMs so pardon the ignorance), with spaces and punctuation

Bash allows it

echo echo hello > "dear computer, please output the word \"hello\". thank you"
chmod +x "dear computer, please output the word \"hello\". thank you"
"dear computer, please output the word \"hello\". thank you"

That might make sense if I was using the scripts to communicaate with a another person, or if I intended other persons besides me to use the scripts

But I'm doing neither of those things. The scripts are for communicating with a computer and are intended to be used only by me

UNIX allows anyone to rename any file to whatever they want. The UNIX user is free to pursue their own preferences in naming, whatever those may be
by gus_massa | 2026-02-07 18:21:55+00:00
Has someone run a test on students? I've seen a lot of claims, but most dessapear when the students take an exam in a controlled environment.

> The rest of the day is devoted to “life skill workshops,” which can mean climbing 40-foot rock walls, assembling a piece of IKEA furniture or solving a Rubik’s Cube.

Has someone run a test on the ability of the students to solve the Rubik's cube? Is it a "life skill"?
by srcreigh | 2026-02-07 18:22:41+00:00
This is just sleight of hand.

In this model the spec/scenarios are the code. These are curated and managed by humans just like code.

They say "non interactive". But of course their work is interactive. AI agents take a few minutes-hours whereas you can see code change result in seconds. That doesn't mean AI agents aren't interactive.

I'm very AI-positive, and what they're doing is different, but they are basically just lying. It's a new word for a new instance of the same old type of thing. It's not a new type of thing.

The common anti-AI trope is "AI just looked at <human output> to do this." The common AI trope from the StrongDM is "look, the agent is working without human input." Both of these takes are fundamentally flawed.

AI will always depend on humans to produce relevant results for humans. It's not a flaw of AI, it's more of a flaw of humans. Consequently, "AI needs human input to produce results we want to see" should not detract from the intelligence of AI.

Why is this true? At a certain point you just have Kolmogorov complexity, AI having fixed memory and fixed prompt size, pigeonhole principle, not every output is possible to be produced even with any input given specific model weights.

Recursive self-improvement doesn't get around this problem. Where does it get the data for next iteration? From interactions with humans.

With the infinite complexity of mathematics, for instance solving Busy Beaver numbers, this is a proof that AI can in fact not solve every problem. Humans seem to be limited in this regard as well, but there is no proof that humans are fundamentally limited this way like AI. This lack of proof of the limitations of humans is the precise advantage in intelligence that humans will always have over AI.
by senordevnyc | 2026-02-07 18:22:45+00:00
The whole point is that you can't 100% trust the LLM to infer your intent with accuracy from lossy natural language.

Then it seems like the only workable solution from your perspective is a solo member team working on a product they came up with. Because as soon as there's more than one person on something, they have to use "lossy natural language" to communicate it between themselves.
by necovek | 2026-02-07 18:23:07+00:00
Somebody mentioned it elsewhere, but it is a security risk: if you end up in a directory that's not under your control, and you do a "ls", it might execute "./ls" instead of /usr/bin/ls, and that can be doing anything, including piping your ~/.ssh/id_* to a remote server.

This can also happen by downloading something off the internet (git clone, or tar xz foo.tar.gz), or on a multi-user system (eg. someone can put any of these common commands into /tmp/ and wait for you to drop into it and try a "ls" there) — if you have any untrusted content anywhere, you are exposed.
by harshalone | 2026-02-07 18:23:16+00:00
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by pkal | 2026-02-07 18:24:53+00:00
That isn't totally true, even on Linux we have had https://jmvdveer.home.xs4all.nl/en.algol-68-genie.html for years.

Also, most languages trace back to ALGOL 60 (the C family tree goes ALGOL 60 -> BCPL -> CPL -> B -> new B -> C -> ANSI C -> ..., though there was some influence such as the idea of "casting", but apparently C only has a castrated version of what ALGOL 68 had) and Pascal is if anything negativly influenced by ALGOL 68 due to Wirth's disagreements with van Wijngaarden: https://dcreager.net/people/wirth/1968-closing-word/.
by 9dev | 2026-02-07 18:25:42+00:00
> Because I deny that? It's not fun for me.

I totally emphasise as a fellow developer, but I doubt you realise what an incredibly privileged position it is to just refuse working if you don't have fun doing it. And it doesn't really make for a convincing argument to keep you employed either.

> Why not? If that makes enough money to keep going.

If all other competing carpenters use power tools, you're going to loose contracts. We've had a few incredibly easy decades as software developers where market pressure wasn't really a thing, but that is about to change when the cost of producing code drops considerably.

> You might argue that in theoretical ideal market companies who're not utilizing every possible trick to improve productivity (including AI) will lose competition […]

You're moving the goalposts here. We're not talking about wringing every last drop of efficiency out of employees. We're talking about businesses not tolerating paying for licenses for AI agents to enable developers to sip Lattés while their computer does their job. That's a fundamentally different proposition.
by harrisi | 2026-02-07 18:26:17+00:00
The aspect of "potentially secure/stable code" is very interesting to me. There's an enormous amount of code that aren't secure or stable already (I'd argue virtually all of the code in existence).

This has already been a problem. There's no real ramifications for it. Even for something like Cloudflare stopping a significant amount of Internet traffic for any amount of time is not (as far as I know) investigated in an independent way. There's nobody that is potentially facing charges. However, with other civil engineering endeavors, there absolutely is. Regular checks, government agencies to audit systems, penalties for causing harm, etc. are expected in those areas.

LLM-generated code is the continuation of the bastardization of software "engineering." Now the situation is not only that nobody is accountable, but a black box cluster of computers is not even reasonably accountable. If someone makes a tragic mistake today, it can be understood who caused it. If "Cloudflare2" comes about which is all (or significantly) generated, whoever is in charge can just throw their hands up and say "hey, I don't know why it did this, and the people that made the system that made this mistake don't know why it did this." It has been and will continue to be very concerning.
by charcircuit | 2026-02-07 18:26:25+00:00
An invasion, or at the very least a replacement of the people and culture of a country being done legally does not mean it is not a problem. And giving more political power to the people who are coming in and outbreeding you will accelerate the timeline of the issue and weaken the power of the ones who can stop it. Policies related to birth rate need to be thought out very carefully as you can incentivize the wrong thing.
by xkriva11 | 2026-02-07 18:26:28+00:00
Smalltalk offers several excellent features for LLM agents:

- Very small methods that function as standalone compilation units, enabling extremely fast compilation.

- Built-in, fast, and effective code browsing capabilities (e.g., listing senders, implementors, and instance variable users...). This makes it easy for the agent to extract only the required context from the system.

- Powerful runtime reflectivity and easily accessible debugging capabilities.

- A simple grammar with a more natural, language-like feel compared to Lisp.

- Natural sandboxing
by redohmy | 2026-02-07 18:26:44+00:00
Are your "empty" GPUs actually leaking proprietary data?

Most enterprise security protocols are built for the era of HDDs and SSDs. But in the age of AI, your NVIDIA H100s and A100s are the new data-bearing frontiers.

The misconception that GPUs are "stateless" is a legacy mindset. Recent research into vulnerabilities like LeftoverLocals proves that uninitialized GPU memory can leak significant data across user boundaries—up to 181 MB per query.

If you are decommissioning a cluster, a simple factory reset isn't enough to satisfy NIST 800-88 compliance. You need:

VRAM Sanitization: Overwriting memory buffers to eliminate data remanence.

Firmware Verification: Flashing BIOS to remove custom configurations.

Documented Chain of Custody: Serial-level tracking to protect your brand from $60M-level liability.

Don't let your high-performance hardware become a high-performance liability.

Read the full deep dive here: https://www.buysellram.com/blog/does-gpu-vram-pose-a-securit...