MurphyA/hacker-news huggingface dataset:
by epistasis | 2026-02-05 03:35:26+00:00
They are already selling ads, why would you think they wouldn't be raising revenue on the news side? Your argument that they wouldn't take money if it's not coming from the "core business" does not make sense economically. If your argument is that they wouldn't sell editorial selection of article topics, well, they did it publicly when they decided to report on the sale of a full page ad. Placement of articles on topics selected from the outside is usually far more discreet, with the proper PR firms mediating the selection, but the NYTimes is notorious for doing this.
by evanelias | 2026-02-05 03:36:10+00:00
For schema changes, it absolutely can, for every situation except table renames or column renames.

That might sound like a major caveat, but many companies either ban renames or have a special "out-of-band" process for them anyway, once a table is being used in production. This is necessary because renames have substantial deploy-order complexity, i.e. you cannot make the schema change at the same exact instant as the corresponding application change, and the vast majority of ORMs don't provide anything to make this sane.

In any case, many thousands of companies use declarative schema management. Some of the largest companies on earth use it. It is known to work, and when engineered properly, it definitely improves development velocity.
by sien | 2026-02-05 03:36:43+00:00
Federal Receipts as Percent of Gross Domestic Product has been roughly stable for more than half a century.

https://fred.stlouisfed.org/series/FYFRGDA188S

The top quintile of income earners in the US pay 34% of all taxes. The next quintile 26% .

https://taxfoundation.org/research/all/federal/who-pays-taxe...

US Federal spending was 7 Trn in 2025. This is surely enough to fund things.

https://fiscaldata.treasury.gov/americas-finance-guide/feder...

That is more than the total GDP of any country except China and the US itself.
by akovaski | 2026-02-05 03:36:49+00:00
I think that Gemini regularly generates inane metaphors like the above. As an example, here's a message that it sent me when I was attempting to get it to generate a somewhat natural conversation:

----

Look, if you aren't putting salt on your watermelon, you’re basically eating flavored water. It’s the only way to actually wake up the sweetness. People who think it’s "weird" are the same ones who still buy 2-in-1 shampoo.

Anyway, I saw a guy at the park today trying to teach a cat to walk on a leash. The cat looked like it was being interrogated by the FBI, just dead-weighting it across the grass while he whispered "encouragement."

Physical books are vastly superior to Kindles solely for the ability to judge a stranger's taste from across a coffee shop. You can’t get that hit of elitism from a matte gray plastic slab.

----

This was with a prompt telling it to skip Reddit-style analogies.
by November_Echo | 2026-02-05 03:37:41+00:00
> Later my boss told me not to do that again because it caused havoc with schedules and such.

Did you talk to anyone about your plans before you brought in the demo or let them know they were solved problems? Often these sorts of reactions come down to your boss not wanting their team to lose their jobs because of the perception that it can all be handled by one person who's happy to work weekends.
by eudamoniac | 2026-02-05 03:37:45+00:00
Listen... I'm just not going to use AI. This is a choice you can make kind of easily. I don't know why we have ten threads per day about AI angst. Just don't use it.

"But I will be left behind!" No you won't. A top 20 percentile dev is not being left behind by the 80% with AI. You'll drop to average, worst case. Unironically just get good.
I outperformed Enterprise Engines by 225,000x on a $50 CPU. Here is the data
by iseph | 2026-02-05 03:38:07+00:00
MANIFESTO: The End of the Era of Mass and the Dawn of #MasslessCode
The software industry is suffering from a terminal case of complacency. We’ve been sold a lie: that to process more, we need "more"—more RAM, more cores, more cloud instances, more budget. Inefficiency has been rebranded as a business model.

As engineers, we have failed. We have accepted that a DMN decision engine—a structure of pure logic—should be a "Tank": a bloated monolith dragging gigabytes of unnecessary libraries and latencies measured in shameful minutes.

Today, Project Velo reclaims the honor of the silicon.

The Test: Science vs. Bureaucracy
To prove that efficiency is a programmer’s obligation and not a hardware luxury, we conducted a head-to-head benchmark:

The Battlefield: 5,000 DMN rules of real-world business complexity.

The Stress Load: 100,000 unique test cases processed sequentially.

The Rival (The Tank): Camunda DMN Engine running on an optimized JVM within a 14-thread Enterprise Server.

Our Weapon (Project Velo): Native C++ architecture, built under the #MasslessCode paradigm.

The Disruption Report
Camunda (Standard): 1,915,223 ms (~32 min) | 1.25 GB RAM | 14 Threads.

Project Velo (Multi-Core): 8.50 ms | 0.49 KB RAM | 4 Threads.

Factor: 225,320x Faster.

Why They Failed (And Why Velo Wins)
The "Java-lovers" and defenders of infinite abstraction have forgotten that memory is not free. Every time your Garbage Collector kicks in, your system stops. Every time your JVM creates an unnecessary object, the processor's cache screams in agony.

Project Velo doesn’t "manage" memory; it lives within it. It doesn’t "abstract" the hardware; it orchestrates it. We have proven that power doesn't come from a $10,000 server, but from knowing exactly what to do with every single clock cycle.

The Final Humiliation: The Toaster vs. The Tank
Here is the fact that will break their hearts: Velo didn't run on a server. It ran on an AMD Athlon 3000G. An entry-level, $50 office "toaster."

While corporate giants need a fleet of tanks just to cross a river, we cross it in milliseconds on a racing bike. If your software requires a server cluster to do what we do on a budget CPU while sipping coffee, your architecture is obsolete.

Efficiency is non-negotiable. Code must be lean. Code must be #Massless.

code with core(s) ||

#ProjectVelo #MultiCore #MasslessCode #Performance
by zaptheimpaler | 2026-02-05 03:38:41+00:00
This is an incredibly broad statement that just isn’t true in a million cases. Last co we migrated all of our observability from Datadog to Grafana/AMP because it’s much much cheaper. The vendor can charge some premium over the cost to build/maintain but not infinity. SaaS is going to have to get dramatically cheaper to compete with the lower cost of building your own.
by tgma | 2026-02-05 03:39:20+00:00
Mac minis out of stock because of OpenClaw?

Nah if they are actually out of stock (I've only seen it out of stock at exceptional Microcenter prices; Apple is more than happy to sell you at full price) it is because there's a transition to M5 and they want to clear the old stock. OpenClaw is likely a very small portion of the actual Mac mini market, unless you are living in a very dense tech area like San Francisco.

One thing of note that people may forget is that the models were not that great just a year ago, so we need to give it time before counting chickens.
by yencabulator | 2026-02-05 03:39:22+00:00
Kilo (chili-/chilo-/*kʰehliyoi) is an Ancient Greek/Proto-Hellenic word literally translated as "one thousand". The word can be traced back to Proto-Indo-European, which means it's as old as any language we're aware of, though Proto-Hellenic is when the meaning was fixed to 1000.
by b1temy | 2026-02-05 03:40:01+00:00
> most tech debt isn’t actually created in the code, it’s created in product meetings. Deadlines. Scope cuts.

> When asked what would help most, two themes dominated

> Reducing ambiguity upstream so engineers aren’t blocked...

I do wonder how much LLMs would help here, this seems to me at least, to be a uniquely human problem. Humans (Managers, leads, owners, what have you) are the ones who interpret requirements, decide deadlines, features and scope cuts and are the ones liable for it.

What could an LLM do to reduce ambiguity upstream? If it was trained with information on requirements, this same information could be documented somewhere for engineers to refer to. If it were to hallucinate or "guess" an answer without talking to a person for clarification, and which might turn out to not be correct, who would be responsible for it? imo, the bureaucracy and waiting for clarification mid-implementation is a necessary evil. Clever engineers, through experience, might try implement things in an open way that can be easily changed for future changes they predict might happen.

As for the second point,

> A clearer picture of affected services and edge cases

> three categories stood out: state machine gaps (unhandled states caused by user interaction sequences), data flow gaps, and downstream service impacts.

I'd agree. Perhaps when a system is complex enough, and a developer is laser focused on a single component of it, it is easy to miss gaps when other parts of the system are used in conjunction with it. I remember a while ago, it used to be a popular take that LLMs were a useful tool for generating unit tests, because of their usual repetitive nature and because LLMs were usually good at finding edge cases to test, some of which a developer might have missed.

---

I will say, it is refreshing to see a take on coding assistants being used on other aspects instead of just writing code, which as the article pointed out, came with its own set of problems (increase Inefficiencies in other parts of the development lifecycle, potential AI-introduced security vulnerabilities, etc.)
by tastyfreeze | 2026-02-05 03:40:15+00:00
Nobody ever paid 90% taxes. There were tax rates that high but lots of ways to avoid it same as now.

If you want a fair tax that treats everybody equally you want a flat consumption tax. No tax to make money. Just taxed when you spend money. Rich people spend more money so they pay more taxes. It can't be avoided by taking a dollar salary or using assets as equity for loans that dont get taxed.

As an aside, billionaires pay the same taxes you do on income. Demanding a wealth tax on billionaires is foolish. Every tax ever devised was sold as a tax on the rich. Look where we are now, forced to give a third or more of our labor to an entity that half the country likes on a good year.
by jorvi | 2026-02-05 03:43:37+00:00
My mother did, for Christmas. It was a goose that ended up being raw in a lot of places.

I then pointed out this same inconsistency to her, and that she shouldn't put stock in what Gemini says. Testing it myself, it would give results between 47c-57c. And sometimes it would just trip out and give the health-approved temperature, which is 74c (!).

Edit: just tested it again and it still happens. But inconsistency isn't a surprise for anyone who actually knows how LLMs work.
by nobody9999 | 2026-02-05 03:45:01+00:00
>It is much easier to get by not paying for NYT by using stuff like https://periscope.corsfix.com/ for sure. But it is a big inconvenience. WSJ is much more aggressive with it.

While not made specifically for that purpose, this extension[0][1] does a nice job without a lot of hassle, and it makes such pages accessible to others with a URL you can share. The downside is that dynamic content isn't supported.

[0] https://addons.mozilla.org/en-US/firefox/addon/archive-page/

[1[ https://github.com/JNavas2/Archive-Page
by Nathanba | 2026-02-05 03:45:17+00:00
I sure hope I never have to hunt down any GTM options myself soon and I can tell the AI to do what it should be doing. However AI adoption may be getting slowed down by profit motives because what Google should have already been doing is letting me git clone the entirety of GTM with all its configs to a local folder so I can treat it like code because it is code. The difficulty with AI adoption will be to make all products be like this so they can interact on a code level instead of me having to press buttons in different UIs to make thing shappen. E.g cloudflare should be letting me git clone its entire config, everything I did in the dashboard, to my folder too.
by Yash16 | 2026-02-05 03:47:33+00:00
I’m building the app https://picxstudio.com
using Claude Code. It’s an AI image-generation site.
I tried using a lightweight LLM to write prompts, but Claude Code with Claude Opus 4.5 writes prompts automatically without even asking.
It just adds proper lighting and better details by default.
I’ve noticed a huge difference in the generated images — Claude Opus 4.5 prompts are way better.
by panarky | 2026-02-05 03:47:41+00:00
Other than the NYT and WSJ, the only national example I can think of is The Guardian's US operation, but that one is supported by a trust plus recurring donations from readers.

There are some good regional examples that show people will still pay enough for rigorous, old-school, fact-checked journalism to make it sustainable.

Minneapolis Star Tribune: ~200 newsroom staff, roughly $220M annual revenue, solidly profitable, seven Pulitzers.

Seattle Times: ~600 employees (not sure how many in the newsroom), marginally profitable after paying legacy pension obligations, nine Pulitzers.

Guardian US: ~110 editorial staff in the US, no subscribers but ~270,000 recurring and ~170,000 annual one-time donations, one Pulitzer but maybe that one should be shared with Snowden.

404media: tiny, 5 people, but solid investigative journalism, national distribution, and some pretty impressive scoops, and it makes a profit from subscriptions.
by jorvi | 2026-02-05 03:48:40+00:00
What do you mean, "are you sure"? I literally saw and see it happen in front of my eyes. Just now tested it with slight variations of "ideal temperature waterfowl cooking", "best temperature waterfowl roasting", etc. and all these questions yield different answers, with temperatures ranging from 47c-57c (ignoring the 74c food safety ones).

That's my entire point. Even adding an "is" or "the" can get you way different advice. No human would give you different info when you ask "what's the waterfowl's best cooking temperature" vs "what is waterfowl's best roasting temperature".
by phamilton | 2026-02-05 03:48:44+00:00
Maybe I expressed that clumsily.

With historical development, investing in hypotheticals can be wasteful. Make the fewest assumptions until you get real user feedback.

With AI, we make more decisions upfront. Being wrong about those decisions has a low cost because the investment in implementation is cheap. We are less worried about building the wrong things because we can just try again quickly. It's cheap to be wrong.

The more decisions we make upfront, the more hands-off we can be. A shallow set of decisions might stall out earlier than a deeper set of decisions could. So we need to think through things more deeply. So we need to think more.
by Analemma_ | 2026-02-05 03:49:20+00:00
No they can’t, states cannot interfere with federal law enforcement in any way. They can refuse to help (and even that is controversial), but they cannot impede. Remember, it’s not like Trump and ICE are going to be announcing that they intend to interfere with elections, they’ll say it’s legitimate law enforcement against a credible threat, and state interference with Federal law enforcement against “credible threats” is completely illegal.

Years down the road, maybe some judge will rule ICE’s actions violated voters’ Constitutional rights, but who cares? The standard punishment for that is a stern “don’t do it again”. If someone is convicted because of a rights violation, their conviction might be overturned, but that’s not what would happen here: it would just be intimidation and harassment to move vote totals and no conviction to be reversed.
by safety1st | 2026-02-05 03:49:42+00:00
The comparison to the dotcom bubble isn't without merit. As a technology in terms of its applications though I think the best one to compare the LLM with is the mouse. It was absolutely a revolution in terms of how we interact with computers. You could do many tasks much faster with a GUI. Nearly all software was redesigned around it. The story around a "conversational interface" enabled by an LLM is similar. You can literally see the agent go off and run 10 grep commands or whatever in seconds, that you would have had to look up.

The mouse didn't become some huge profit center and the economy didn't realign around mouse manufacturers. People sure made a lot of money off it indirectly though. The profits accrued from sales of software that supported it well and delivered productivity improvements. Some of the companies who wrote that software also manufactured mice, some didn't.

I think it'll be the same now. It's far from clear that developing and hosting LLMs will be a great business. They'll transform computing anyway. The actual profits will accrue to whoever delivers software which integrates them in a way that delivers more productivity. On some level I feel like it's already happening, Gemini's well integrated into Google Drive, changes how I use it, and saves me time. ChatGPT is just a thing off on the side that I chat randomly with about my hangover. Github Copilot claims it's going to deliver productivity and sometimes kinda does but man it often sucks. Easy to infer from this info who my money will end up going to in the long run.

On diversification, I think anyone who's not a professional investor should steer away from picking individual stocks and already be diversified... I wouldn't advise anyone to get out of the market or to try and time the market. But a correction will come eventually and being invested in very broad index funds smooths out these bumps. To those of us who invest in the whole market, it's notable that a few big AI/tech companies have become a far larger share of the indices than they used to be, and a fairly sure bet that one day, they won't be anymore.
by orchidfiles | 2026-02-05 03:50:53+00:00
Try promoting your project not with conventional SEO in search engines (GSC), but with the help of AI (chatgpt, perplexity, etc.). However, if you create a blog or articles on your website, they may not rank in AI chats. However, if you post the same content on other high-trust websites, these articles will appear in AI overviews within a week, including Google AI overviews. Along with the answer to the user's question, AI will take a link to your service from the article and offer it to the user. You can get much more traffic through gpt & perplexity than through Google search.
by b00ty4breakfast | 2026-02-05 03:51:11+00:00
I always think of the Little League World Series when I read about stuff like this; these kids are often peaking early and so rarely make it to the highest levels as an adult. This is either because they quit advancing at the same rate or they've destroyed their bodies before they get to high school.

I think there's been like a handful LLWS winners who have done anything in the MLB and even fewer who have reached the top of pros.
by kstrauser | 2026-02-05 03:53:52+00:00
I wasn’t politically savvy enough to do that. Honestly, I don’t want to be. The reality was that the project really could have been done in a month by a couple of people. It got turned into an enterprise project with multiple unaligned teams with Gantt charts and milestones and everything.

Again, and I can’t emphasize this enough, for a Django CRUD app. It was a 4 person-week project turned into a major ordeal. No one should have lost their job; they should have been put to work doing the thousand other more productive things they could’ve been doing instead.
Show HN: Buquet – Durable queues and workflows using only S3
by h0rv | 2026-02-05 03:54:19+00:00
buquet (bucket queue) is a queue and workflow orchestration tool using only S3-compatible* object storage. S3 is the control plane making it much simpler than alternatives. This does come with tradeoffs (see docs), but I do believe there is a niche it can serve well.

https://horv.co/buquet.html
https://github.com/h0rv/buquet

* see https://github.com/h0rv/buquet/blob/main/docs/guides/s3-comp...
by alex_w_systems | 2026-02-05 03:54:33+00:00
I think the interesting tension here is between capability and trust.

An agent that can truly “use your computer” is incredibly powerful,
but it's also the first time the system has to act as you, not just for you.
That shifts the problem from product design to permission, auditability,
and undoability.

Summarizing notifications is boring, but it’s also reversible.
Filing taxes or sending emails isn’t.

It feels less like Apple missing the idea, and more like waiting
until they can make the irreversible actions feel safe.
by angiolillo | 2026-02-05 03:55:29+00:00
I'm curious what makes you think the solutions of the past have been forgotten or that they were somehow more reliable? (They're certainly simpler, I'll give you that!)

I have printouts of school/camp calendars taped to the wall, a weekly planner on the kitchen whiteboard, paper grocery lists on the fridge, and a pocket notebook for capturing random tasks. I used to believe that some lifehack, process, methodology, app, or modern jeejah would finally solve my organization problems. But as I got older I made peace with the fact that they're all limited by the same weak link -- me.
Ask HN: Is Connecting via SSH Risky?
by atrevbot | 2026-02-05 03:56:25+00:00
I have been managing websites for a while and usually utilize SSH connections to login to, deploy code to, and otherwise remotely access the hosting servers.

I was recently informed that a client I work with considers that a legal risk.

If the SSH connection is set to disallow passwords and only authorize via SSH keys, how big of a risk is this?
by harry8 | 2026-02-05 03:57:05+00:00
Tiger woods. I can't think of any tennis player who has been in the top 100 for the past few decades who didn't commit to it totally as a young child. Start tennis at 10? Too old. Swimmers. Has anyone stumbled into sporting greatness from being outside the top 5%? Or 1% when they hit adulthood?

So what is being said? A huge amount of elite success is in the hardware, i.e. the body &/or brain. These go through rather large changes between ages 10 an 18. Puberty. This shakes up the ordering among those who showed enough promise to have already committed to becoming elite.

What am I missing here? Seems like this research is nothing more than "Kids change through puberty, the nature and sizes of the changes are a bit of a lottery for each kid." Much like the the genetic factors are also a lottery so you can't reliably predict who is going to be great from the results of their parents. (But if your parents are both 5ft, the NBA seems an unlikely destination for you).
by charcircuit | 2026-02-05 03:57:06+00:00
I am saying that if you have an outlet where your posts are getting 10 to 20 thousand impressions, the most impressions out of any other channel of communication you should not abandon it.

Being on social media is very relevant due to both content discovery algorithms being able to connect people who may be interested in the project with the project itself and because social media sites can have things go viral outside of your own personal reach. Your post can reposted or spread by other accounts easier if its originating from the platform itself instead of hopping someone sees it and copies onto the platform.
by bandrami | 2026-02-05 03:57:17+00:00
They're in series A right now, so most likely yes they will fail like most new businesses do. Internal chat is a hugely competitive field with multiple large players (and Teams has had Copilot for a while now). So, I wish them the best, but this is pretty much exactly the kind of "existing product + AI" mashups that will have a tendency to burn out over the next couple of years, just like "our old business but with .com at the end" did back in 1999-2000.