MurphyA/hacker-news huggingface dataset:
by xyzzy123 | 2026-02-18 02:25:02+00:00
Even if code gets cheaper, running your own versions of things comes with significant downsides.

Software exists as part of an ecosystem of related software, human communities, companies etc. Software benefits from network effects both at development time and at runtime.

With full custom software, you users / customers won't be experienced with it. AI won't automatically know all about it, or be able to diagnose errors without detailed inspection. You can't name drop it. You don't benefit from shared effort by the community / vendors. Support is more difficult.

We are also likely to see "the bar" for what constitutes good software raise over time.

All the big software companies are in a position to direct enormous token flows into their flagship products, and they have every incentive to get really good at scaling that.
by DaedalusII | 2026-02-18 02:25:05+00:00
when the work involves navigating a bunch of rules with very ambiguous syntax, AI will automate them to the point computers automated rules based systems with very precise syntax in the 1990s

https://hazel.ai/tax-planning

this software (which i am not related to or promoting) is better at investment planning and tax planning than over 90% of RIAs in the US. It will automate RIA to the point that trading software automated stock broking. This will reduce the average RIA fee from 1% per year to 0.20% or even 0.10% per year just like mutual fund fees dropped in the early 00s
by joemi | 2026-02-18 02:25:23+00:00
I missed that sentence too. I guess the large heading starting with "(1)" drew my eyes first and felt like the natural place to start reading, while the short sentence or two above it in smaller text subconsciously felt skippable (and was skipped). Even when I went back to read the first sentence, I had to kind of force myself to read the stuff above the first large heading. How odd!
by yodsanklai | 2026-02-18 02:25:32+00:00
I'm a SWE who's been using coding agents daily for the last 6 months and I'm still skeptical.

For my team at least, the productivity boost is difficult to quantify objectively. Our products and services have still tons of issues that AI isn't going to solve magically.

It's pretty clear that AI is allowing to move faster for some tasks, but it's also detrimental for other things. We're going to learn how to use these tools more efficiently, but right now, I'm not convinced about the productivity gain.
by dang | 2026-02-18 02:25:58+00:00
As it happens, a great counterexample has been on the frontpage for hours:

Show HN: AsteroidOS 2.0 – Nobody asked, we shipped anyway - https://news.ycombinator.com/item?id=47051852 - Feb 2026 (34 comments)

What a bummer it would be to lose excellent posts by new users. They do happen!
by ckarani | 2026-02-18 02:26:28+00:00
Foundation Models are on-device in iOS 26. The inference story is real. The workflow story isn't — there's no native Swift runtime for reliable agent graphs. I built one.

The insight: borrow Bulk Synchronous Parallel execution from distributed systems. Nodes run concurrently, writes are held until the frontier completes, then committed atomically. The next step sees a clean snapshot. Same inputs → byte-identical event streams, every time. Deterministic by construction, not by convention.

That discipline is unforgiving. Every sort in the codebase uses utf8.lexicographicallyPrecedes — never Swift's locale-aware String.<. One wrong comparator and replay breaks across machines. The graph version is a SHA-256 hash of the full topology. Checkpoints hard-reject hash mismatches. You cannot accidentally resume against a modified graph.
Swift 6 strict concurrency is a design constraint, not an afterthought. Node closures run in a static func that physically can't capture the actor — the compiler enforces isolation, not a comment in the README.

Interrupt/resume, fan-out/join, and a SwiftUI-style workflow DSL are all first-class primitives.

https://github.com/christopherkarani/Hive
by greygoo222 | 2026-02-18 02:26:30+00:00
I guarantee you I've spent more time thinking about this than you have.

Massive decreases in population change culture. The Western cultural context we have today won't just magically persist, converting new people, until we run out of people. At worst, we'll end up in a world where the majority of the population consists of the descendants of current high-fertility subcultures. Even that is extremely unlikely. Fertility rates only become a population-level problem a few generations down the line, at which point we are almost guaranteed to have artificial wombs and other technology that changes the dynamics of reproduction entirely.

Fertility is worth worrying about because it may cause fewer resources for the elderly, particularly in some acutely affected nations. It is not an extinction risk.
by Haven880 | 2026-02-18 02:26:32+00:00
I think both. Most organizatuons lack someone like Steve Jobs to prime their product lines. Microsoft is a good example where you see their products over the years are mostly meh. Then meetings are pervasive and even more so in most companies due to msteam convenience. But currently they faced reduced demands due softer market as compare 2-3 years ago. If you observed that no effect while they layoff many and revenue still hold or at least no negative growth, I would surmise that AI is helping. But in corporate, it only counta if directly contributed sales numbers.
by crazygringo | 2026-02-18 02:26:38+00:00
Just to be clear, the article is NOT criticizing this. To the contrary, it's presenting it as expected, thanks to Solow's productivity paradox [1].

Which is that information technology similarly (and seemingly shockingly) didn't produce any net economic gains in the 1970's or 1980's despite all the computerization. It wasn't until the mid-to-late 1990's that information technology finally started to show clear benefit to the economy overall.

The reason is that investing in IT was very expensive, there were lots of wasted efforts, and it took a long time for the benefits to outweigh the costs across the entire economy.

And so we should expect AI to look the same -- it's helping lots of people, but it's also costing an extraordinary amount of money, and the few people it's helping is currently at least outweighed by the people wasting time with it and its expense. But, we should recognize that it's very early days, and that productivity will rise with time, and costs will come down, as we learn to integrate it with best practices.

[1] https://en.wikipedia.org/wiki/Productivity_paradox
by lich_king | 2026-02-18 02:26:38+00:00
> making slides/decks to communicate those thoughts,

That use case is definitely delegated to LLMs by many people. That said, I don't think it translates into linear productivity gains. Most white collar work isn't so fast-paced that if you save an hour making slides, you're going to reap some big productivity benefit. What are you going to do, make five more decks about the same thing? Respond to every email twice? Or just pat yourself on the back and browse Reddit for a while?

It doesn't help that these LLM-generated slides probably contain inaccuracies or other weirdness that someone else will need to fix down the line, so your gains are another person's loss.
Other money making uses for the DGX Spark?
by JerichoJones | 2026-02-18 02:27:17+00:00
I just got this today and have it setup with vsCode. I was thinking it would be nice to make use of this to generate some income when I'm not using it for dev.
The first thought was crypto but I have been out of that business for a few years. Searches on the subject were no help.

I'm looking for ideas.
Thanks!
jj
by JohnBooty | 2026-02-18 02:27:28+00:00
At least in the US, those "deluxe" cabs with motion just never seemed like a viable deal to me as a kid/teenager visiting arcades.

It was like, $1 per game compared to $0.25 or $0.50 for a normal cabinet.

As a young person with limited income, it DEFINITELY mattered to me... I preferred to sacrifice a little bit of motion and enjoy 2x or 4x the playtime on something else. I mean realistically you'd be spending $20 an hour or more if you stuck to deluxe cabinets. At that point (according to my teenage mind) I was basically halfway to buying a home console game that I could keep forever.

Operators really should have priced those deluxe cabinets the same as regular games during off-peak hours.
by dimitri-vs | 2026-02-18 02:28:00+00:00
IMO Copilot was "we need to give these people rope, but not enough for them to hang themselves". A non technical person with no patience and access to a real AI agent inside a business is a bull in a china shop. Copilot Cowork is the closest thing we have to what Copilot should have been and is only possible now because models finally got good enough to be less supervised.

FWIW Gemini inside Google apps is just as bad.
by cmiles8 | 2026-02-18 02:28:10+00:00
I like AI and use it daily, but this bubble can’t pop soon enough so we can all return to normally scheduled programming.

CEOs are now on the downside of the hype curve.

They went from “Get me some of that AI!” after first hearing about it, to “Why are we not seeing any savings? Shut this boondoggle down!” now that we’re a few years into bubble, the business math isn’t working, and they only see burning piles of cash.
by dakolli | 2026-02-18 02:28:14+00:00
Do you really think the ruling class has any plans to allow that to happen... There's a reason so much surveillance tech is being rolled out across the world.

If the world needs 1/3 of the labor to sustain the ruling class's desires, they will try to reduce the amount of extra humans. I'm certain of this.

My guess is during this "2nd industrial revolution" they will make young men so poor through the alienation of their labor that they beg to fight in a war. In that process they will get young men (and women) to secure resources for the ruling class and purge themselves in the process.
by n_u | 2026-02-18 02:28:17+00:00
Original paper https://www.nber.org/system/files/working_papers/w34836/w348...

Figure A6 on page 45: Current and expected AI adoption by industry

Figure A11 on page 51: Realised and expected impacts of AI on employment
by industry

Figure A12 on page 52: Realised and expected impacts of AI on productivity
by industry

These seem to roughly line up with my expectations that the more customer facing or physical product your industry is, the lower the usage and impact of AI. (construction, retail)

A little bit surprising is "Accom & Food" being 4th highest for productivity impact in A12. I wonder how they are using it.
by mathgladiator | 2026-02-18 02:29:07+00:00
I'm no boomer, but I'm building a pipeline to produce books in a variety of genres.

This is one chapter of a book: https://nexivibe.com/writing/chapter_01.html

People that take it seriously, are going to focus on the architecture, universe building, characters, and arc flow and then let the writing be done in a way. The power tools of the cognitive era are arriving.

I'm reading a 500 page sci-fi book and evaluating it, the first 275 pages are fantastic until I can feel the context collapse and it craps the bed.
by toyg | 2026-02-18 02:29:12+00:00
I actually think the opposite will happen. Suddenly, smart AI-enabled juniors can easily match the productivity of traditional (or conscientious) seniors, so why hire seniors at all?

If you are an exec, you can now fire most of your expensive seniors and replace them with kids, for immediate cash savings. Yeah, the quality of your product might suffer a bit, bugs will increase, but bugs don't show up on the balance sheet and it will be next year's problem anyway, when you'll have already gone to another company after boasting huge savings for 3 quarters in a row.
by alexpotato | 2026-02-18 02:29:15+00:00
> Its also worth noting that if you can create a business with an LLM, so can everyone else. And sadly everyone has the same ideas, everyone ends up working on the same things causing competition to push margins to nothing.

This was true before LLMs. For example, anyone can open a restaurant (or a food truck). That doesn't mean that all restaurants are good or consistent or match what people want. Heck, you could do all of those things but if your prices are too low then you go out of business.

A more specific example with regards to coding:

We had books, courses, YouTube videos, coding boot camps etc but it's estimated that even at the PEAK of developer pay less than 5% of the US adult working population could write even a basic "Hello World" program in any language.

In other words, I'm skeptical of "everyone will be making the same thing" (emphasis on the "everyone").
by LPisGood | 2026-02-18 02:29:22+00:00
I’m confused what kind of software engineer jobs there are that don’t involve meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate that, thinking about market positioning, etc?

If you weren’t doing much of that before, I struggled to think of how you were doing much engineering at all, save some more niche extremely technical roles where many of those questions were already answered, but even still, I should expect you’re having those kinds of discussions, just more efficiently and with other engineers.
by Sateeshm | 2026-02-18 02:29:44+00:00
The cell layers constraint led to better art. The detail in the background was minimal and the artists world compensate for it by interesting framing and lighting. Go back and watch one fish two fish or the black widower episodes from early seasons - just incredible animation.

You can see the number of lines drawn go up like crazy around season 10 or so, making it feel less realistic. Coincidentally, the writing also started to get worse around this time.
by ahartmetz | 2026-02-18 02:29:53+00:00
What I think after looking at these numbers is that we need to take the nuclear option - a native (no web stack at all) code review client. Seconds (times 100 or so for one larger review) are not in any way an acceptable order of magnitude to discuss performance of a front-end for editing tens of kilobytes of text. And the slow, annoying click orgy to fold out more common code, a misfeature needed just to work around loading syntax-highlighted text being insanely slow. Git is very fast, text editing is very fast, bullshit frameworks are slow.

I don't think that it would take great contortions to implement a HTML + JS frontend that's an order of magnitude faster than the current crapola, but in practice it... just doesn't seem to happen.
by Aachen | 2026-02-18 02:29:54+00:00
(I agree with you in spirit, namely that GrapheneOS' standards are clearly beyond what most vendors are willing or able to do and a compromise or support of users who want to port the OS might be fitting for the current situation, but notice that the person you replied to never said "minimal", they said "minimum". I'm not a native english speaker but I believe your reading is a value judgement along the lines of "not much work" (in this context) whereas they probably intended it like a statement of fact regarding what the requirements are.)
by kretaceous | 2026-02-18 02:30:08+00:00
Suppose there's the following situation:

Summary A = summarise(message 1 to P)
Summary B = summarise(Summary A, message P+1 to Q)
Summary C = summarise(Summary B, message Q+1 to R)

What does calling lcm_expand(Summary C) do? Does it unroll all messages from message 1 to message R or does it unroll to Summary B and message Q+1 to R?

> volume is potentially arbitrarily large is that one sub-agent can call lcm_expand multiple times - either vertically or horizontally

I'm assuming from this that it's the latter? In that case, that addresses my concern about not blowing up the context window immediately.
by sebmellen | 2026-02-18 02:30:09+00:00
Yeah, but this is self-correcting. Eventually it will get to a point where the data that you use to prompt the LLM will have more signal than the LLM output.

But if you get deep into an enterprise, you'll find there are so many irreducible complexities (as Stephen Wolfram might coin them), that you really need a fully agentically empowered worker — meaning a human — to make progress. AI is not there yet.
by Retric | 2026-02-18 02:30:32+00:00
They don’t do human in the loop at highway speeds.

Further the cars need to safely stop in an emergency without human intervention. There’s no way for the car to first notice a problem, then send a message to a call center which then routes to a human, and for that human to understand the situation, all fast enough to avoid a collision. Even 50ms is significant here let alone several seconds.
by Jonovono | 2026-02-18 02:30:35+00:00
I really want to like obsidian but it’s just unusable (for me)

So I built my own thats a bit more lightweight. Think nvalt meets markdown. thats native, iOS and Mac with I cloud sync, and open source.

Check it out if it sounds interesting!

iOS app is still in review ;(

https://hashy.ink/
by kjellsbells | 2026-02-18 02:31:14+00:00
Maybe experienced people are the L2 cache? And the challenge is to keep the cache fresh and not too deep. You want institutional memory available quickly (cache hit) to help with whatever your CPU people need at that instant. If you don´t have a cache, you can still solve the problem, but oof, is it gonna take you a long time. OTOH, if you get bad data in the cache, that is not good, as everyone is going be picking that out of the cache instead of really figuring out what to do.
Show HN: AIBenchy – Independent AI Leaderboard
by XCSme | 2026-02-18 02:31:35+00:00
Hey HN,
Like many of you, I'm tired of public AI leaderboards that mostly recycle the same saturated/overfitted benchmarks (MMLU, HumanEval, etc.) and often miss fast/cheap variants or real daily pain points.

A couple days ago I launched AIBenchy — a small, opinionated leaderboard running my own custom tests focused on end-user/dev scenarios that actually trip up models today.

Current tests cover categories like:

- Anti-AI Tricks (classic gotchas like "count the Rs in strawberry", logic traps)

- Instruction following & consistency

- Data parsing/extraction

- Domain-specific tasks

- Puzzle solving / edge-case reasoning

Recent additions (just pushed today):

- Reasoning score (new!): A separate judge LLM evaluates the chain-of-thought for efficiency — does it repeat itself, loop, think forever, brute-force enumerate every possibility (looking at you, some Qwen-3.5 runs), or get to the point cleanly? This penalizes "cheaty" high-token reasoning even if the final answer is correct. Goal: reward smart, concise thinking over exhaustive trial-and-error.

- Stability metric: Measures consistency across runs (some models flake on the same prompt).

Right now the leaderboard has ~20 models (Qwen3.5 Plus currently topping it, followed by GLM 5, various GPT/Claude variants, etc.), but it's super early/WIP:

- Manual runs + small test set - No public submission of tests yet (open to ideas!) - Focused on transparency & practical usefulness over massive scale

I'd love feedback from HN:

- What custom tests / gotchas / use-cases should I add next?

- Thoughts on the reasoning score — fair way to judge efficiency, or too subjective?

- Models/variants I'm missing (especially fast/cheap ones ignored elsewhere)?

- Should I let people submit their own prompts/tests eventually?

Thanks for checking it out: https://aibenchy.com

Appreciate any roast/ideas — building this to scratch my own itch.
by agwa | 2026-02-18 02:31:50+00:00
It doesn't comply with one or more root store policies (which all incorporate the Baseline Requirements by reference, which incorporate various specs, such as RFC5280, by reference).

Mozilla root store policy: https://www.mozilla.org/en-US/about/governance/policies/secu...

Chrome root store policy: https://googlechrome.github.io/chromerootprogram/

Apple root store policy: https://www.apple.com/certificateauthority/ca_program.html

Baseline Requirements: https://github.com/cabforum/servercert/blob/main/docs/BR.md

There are countless examples of non-compliant certificates documented in the Bugzilla component I linked above. A recent example: a certificate which was backdated by more than 48 hours, in violation of section 7.1.2.7 of the Baseline Requirements: https://bugzilla.mozilla.org/show_bug.cgi?id=2016672
by snowwrestler | 2026-02-18 02:32:33+00:00
It is unlikely Carr will be FCC chair past January 20, 2029. (If he makes it that long.)

However, all those conservative billionaires will still own their media companies. Expanding the coverage of the equal time rule would hand the next Democratic administration a big club to swing at them.

Hey maybe for his next act, Carr will revive the Fairness Doctrine that was repealed under Reagan.
by cmeacham98 | 2026-02-18 02:33:24+00:00
While the operator did write a post, they did not come forward - they have intentionally stayed anonymous (there is some amateur journalism that may have unmasked the owner I won't link here - but they have not intentionally revealed their identity).

Personally I find it highly unethical the operator had an AI agent write a hitpiece directly referencing your IRL identity but choose to remain anonymous themselves. Why not open themself up to such criticism? I believe it is because they know what they did was wrong - Even if they did not intentionally steer the agent this way, allowing software on their computer to publish a hitpiece to the internet was wildly negligent.
Show HN: DevDay – End-of-day recap for AI coding sessions
by ujjwaljainnn | 2026-02-18 02:33:41+00:00
I built devday because I use multiple AI coding tools (OpenCode, Claude Code, Cursor) and wanted a single command to see what I actually accomplished each day. It reads local session data, cross-references with git commits, and optionally generates standup-ready summaries via OpenAI or Anthropic.

Everything runs locally — no data leaves your machine unless you opt into LLM summaries.

Install with npm install -g devday.

Currently supports OpenCode, Claude Code, and Cursor on macOS. Would love feedback on what other tools to support.
by pandaman | 2026-02-18 02:33:59+00:00
Russia had been under sanctions since 2014 and in January of 2015 its economy was already "in tatters", as reported by Obama in the State of the Union that year. Then, in March of 2022, great Joe Biden proclaimed that he has turned "ruble into rubble". I am sure the 20 packages of sanctions since then destroyed anything that left and it's really just vacuum in place of Russian economy now... Why end the lies if you can call anyone pointing them out a Russian bot?
by beloch | 2026-02-18 02:34:19+00:00
The article suggests that AI-related productivity gains could follow a J-curve. An initial decline, as initially happened with IT, followed by an exponential surge. They admit this is heavily dependent on the real value AI provides.

However, there's another factor. The J-curve for IT happened in a different era. No matter when you jumped on the bandwagon, things just kept getting faster, easier, and cheaper. Moore's law was relentless. The exponential growth phase of the J-curve for AI, if there is one, is going to be heavily damped by the enshitification phase of the winning AI companies. They are currently incurring massive debt in order to gain an edge on their competition. Whatever companies are left standing in a couple of years are going to have to raise the funds to service and pay back that debt. The investment required to compete in AI is so massive that cheaper competition may not arise, and a small number of (or single) winner could put anyone dependent on AI into a financial bind. Will growth really be exponential if this happens and the benefits aren't clearly worth it?

The best possible outcome may be for the bubble to pop, the current batch of AI companies to go bankrupt, and for AI capability to be built back better and cheaper as computation becomes cheaper.