MurphyA/hacker-news huggingface dataset:
by locknitpicker | 2026-01-12 07:15:53+00:00
> I read Effective Modern C++ years ago and was confused exactly like what you describe.

It's been a while since I read it, but if I recall correctly the book focused on special member functions and when the compiler actually stepped in for the developer, not the actual concept of move semantics. Those are different things.

Special member functions is a development experience issue, and covers aspects such as "can I get the compiler going to generate code for me". If you write code that tells the compiler it should not generate move constructors for you, often it ends up generating copy constructors. That's it.
by Lio | 2026-01-12 07:17:10+00:00
Yep I agree, I think people haven’t woken up to that yet. Moore’s Law is only going to make that easier.

I’m surprised by how good the models I can run on my old M1 Max laptop are.

In a year’s time open models on something like a Mac Studio M5 Ultra are going to be very impressive compared to the closed models available today.

They won’t be state of the art for their time but they will be good enough and you’ll have full control.
by KronisLV | 2026-01-12 07:18:02+00:00
> I end up rewriting about 70% of the thing.

Doesn't match my experience, that figure is closer to about 20-40% to me, though a lot of those changes I want are possible by just further prompting OR turning to a different model, or adding some automated checks that promptly fail and the AI can do a few more loops of fixes.

> Other people are just less picky than I am, or they have a less thorough review culture that lets subpar code slide more often.

This is also likely, or you are just doing stuff that is worse represented in the training data, or working on novel things where the output isn't as good. But I'm leaning towards people just being picky about what they view as "good code" (or underspecifying how the AI is supposed to output it) at least roughly since Sonnet 4, since with some people I work with it's just endless and oftentimes meaningless discussions and bikeshedding when in code review.

You can always be like: "This here pattern in these 20 files is Good Code™, use the same collection of approaches and code style when working on this refactoring/new feature."
by oefrha | 2026-01-12 07:18:20+00:00
And on top of that, putting these in AGENTS.md makes no sense whatsoever. You’ll simply waste tokens and confuse the hell out of your agents. I wonder if gp assumed this is another repo of design patterns without reading anything there at all. Pasting a bunch of design patterns into AGENTS.md may not be the brightest idea either but at least that isn’t absurd.
by napkinartist | 2026-01-12 07:19:32+00:00
You are saying the same thing they said -- it doesn't scale. It's not how you build a large factory. They acknowledge this and pretty quickly move on to say that they are aiming for smaller and sustainable.

They even specifically call out why they chose not to use a conveyor based oven in the video.

Basically they believe they can be price reasonable at small scales, small batches. Build process knowledge and expertise over time, and then incrementally scale up after assessing bottlenecks.

I think the route of local sustainable, grow as needed or collaborate to expand capacity is pretty reasonable.
by lmeyerov | 2026-01-12 07:19:38+00:00
We find across our team different people are able to use these things at different levels. Unsurprisingly, more senior coders with both more experience in general and more experience in ai coding are able to do more with ai and get more ambitious things done more quickly.

A bummer is that we have a genai team (louie.ai) and a gpu/viz/graph analytics team (graphistry), and those who have spent the last 2-3 years doing genai daily have a higher uptake rate here than those who aren't. I wouldn't say team 1 is better than team 2 in general: these are tools, and different people have different engineering skill and ai coding skill, including different amounts of time doing both.

What was a revelation for me personally was taking 1-2mo early in claude code's release was to go full cold turkey on manual coding, similar to getting immersed in a foreign language. That forced eliminating a lot of bad habits wrt effective ai coding both personally and in state of our repo tooling. Since then, it's been steady work to accelerate and smooth that loop, eg, moving from vibe coding/engineering to now more eval-driven ai coding loops: https://media.ccc.de/v/39c3-breaking-bots-cheating-at-blue-t... . That takes a LOT of buildout.
by widdershins | 2026-01-12 07:19:42+00:00
That's a sad way to think. I'd like to hope that humanity can improve itself, and that includes building products that are safer, more refined, more beautiful, more performant and more useful. I agree that there's a lot of crap out there, but I still want to believe and strive to make things that are excellent. I'm not ready to give up on that. And yes, I still get annoyed every time my crappy toaster doesn't work properly.
by PeterStuer | 2026-01-12 07:20:23+00:00
"but the open models, especially the ones produced in China, continue to compete (even if they are behind) with frontier models of closed labs"

You will still need hardware to run those open models, and that avenue is far easier to contain and close than stopping code distribution. Expect the war on private/personal compute to ramp up even more significantly than ot already has.
by DonHopkins | 2026-01-12 07:22:02+00:00
And I watched The Flintstones as a very young kid and loved it. And it deeply influenced how I thought cavemen lived. Well done, Hanna-Barbera!

The problem is that Erich von Däniken's "science fiction" was pseudo-scientific claptrap, which he sold as the truth, that perpetuated harmful cultural stereotypes, was patronizingly racist, also plagiarized French author Robert Charroux's "The Morning of the Magicians", and he never admitted he was wrong despite mountains of indisputable evidence.

At least Hanna-Barbera framed The Flintstones as fiction. Yabba Dabba Doo!
by Jennyyyy111 | 2026-01-12 07:22:29+00:00
Hey HN, Happy New Year!

I built TweetGrok Twitter Viewer because Twitter now requires login to view public content, which creates unnecessary friction for researchers, journalists, and casual users.

What it does:

View any public Twitter profile and tweets — no account required.

Search tweets by keywords across public profiles.

Download Twitter videos in MP4 format.

Fully anonymous — no tracking or data collection.

Tech stack:

Next.js 14 (App Router) for fast server-side rendering.

Tailwind CSS for styling.

Hosted on Vercel Edge runtime for low-latency performance.

Twitter API integration via proxy.

Why I built it:
Since Twitter’s 2023 policy changes, even viewing a single public tweet requires an account. This is frustrating for anyone who just wants to quickly check a profile, share a link, or conduct research. TweetGrok removes that barrier while keeping browsing completely private.

It’s been in private beta for a month with positive feedback. Today it’s launching publicly: https://tweetgrok.ai/twitter-viewer

Happy to answer any questions about how it works or its implementation.
by bossyTeacher | 2026-01-12 07:22:57+00:00
>I found it especially ironic being on hacker news how few people seemed to have a hacker mindset when it came to LLMs

You keep using the word "LLMs" as if Opus 4.x came out in 2022. The first iterations of transformers were awful. Gpt-2 was more of a toy and Gpt-3 was an eyebrow-raising chatbot. It has taken years of innovations to reach the point of usable stuff without constant hallucinations. So don't fault devs for the flaws of early LLMs
by Closi | 2026-01-12 07:23:00+00:00
Try learning to vibe code on something totally greenfield without looking at the code and see if it changes your mind. Ignore code quality, “does it work” and “am i happy with the app” are the only metrics.

Code quality is an issue you need to ignore with vibe coding - if code quality is important to your project or you then it’s not an issue. But if you abandon this concept and build things small enough or modular enough then speed gains await!

IMO codebases can be architected for LLMs to work better in them, but this is harder in brownfield apps.
by krupan | 2026-01-12 07:23:57+00:00
"It does not matter if AI companies will not be able to get their money back and the stock market will crash. All that is irrelevant, in the long run."

Seriously? If these were open source tools that anyone could run on their home PC that statement would make sense, but that's not what we are talking about here. LLMs are tools that cost massive amounts of money to operate, apparently. The tool goes away if the money goes away. Fossil fuels revolutionized the world, but only because the cost benefit made sense (at least in the relative short-term).
by elitan | 2026-01-12 07:24:37+00:00
Been using Claude Code to build a small deployment tool (Frost) for exactly this use case. The meta experience is interesting - using an AI agent to build tooling that makes self-hosting easier.

What I've found: Claude Code is great at the "figure out this docker/nginx/systemd incantation" part but the orchestration layer (health checks, rollbacks, zero-downtime deploys) still benefits from purpose-built tooling. The AI handles the tedious config generation while you focus on the actual workflow.

github.com/elitan/frost if curious
by MORPHOICES | 2026-01-12 07:24:37+00:00
After the macOS Tahoe upgrade, I keep missing window resize corners. ~

I was slow to realize why. Although the corner appears substantial, the real area being resized is significantly smaller. Furthermore, because of the larger corner radius, this target lie mostly off-screen.

I have never experienced this before. After using computers for decades, resizing windows became like muscle memory for me. I now miss it at least a few times a day.

What I find interesting is not this particular bug but the pattern.

Here’s a rough framework I’m using to think about it.

The visual and interaction affordance can diverge.

Muscle memory is more delicate than we think.

A little tweak in a hit-target can create daily frustration.

Changes made only for aesthetic purposes have behavioral costs.

There are certain thoughts that might have helped here.

Ensure the interactive region aligns with the visible shape, even if it intrudes.

Slightly expand the resize hit zones near corners since people overshoot anyway.

Implement subtle cursor feedback earlier, before entering the exact pixel zone.

I'm interested to learn how others feel about this tradeoff.

Have you ever encountered regressions where a visual polish fix disrupted a learned behavior?

Is muscle memory a hard constraint that must be followed, or is it something the users should relearn?

What evidence would you look for in these changes to decide they are not working?
by alance | 2026-01-12 07:24:56+00:00
It seems like the choices are:

a) a cloud-based password service (eg 1password) or

b) a local-storage password database (eg pass, KeePassXC)

My preference is not to store personal account details with an internet accessible third-party (but I can see the value in it for an organization).

And with the local solutions, it doesn't really seem pleasant to manage, use, synchronize and backup password databases across multiple machines. Also it seems like you're just one laptop disk dying away from possibly losing credentials.

To be clear I'm not suggesting anybody should use my hacky script - the article is meant to be more like: "well I don't love this, but here's how I do things".

Got another approach?
by _0ffh | 2026-01-12 07:25:09+00:00
Yeah, I think it might be a driver thing (or driver interaction with XFCE code).

After ~10 years of using XFCE, I recently for the first time encountered flickering, after an NVidia driver update. I disabled compositing and it went away. Still happy, but clearly something broke there. Pretty sure someone's trying to fix it, somewhere.
by locknitpicker | 2026-01-12 07:25:36+00:00
> Throwing move is super weird too. I believe that it was a mistake to not treat user move like C++11 destructors and default to noexcept(true) on them. But it is what it is.

I think you're missing a fair deal of insight into the issue.

The move semantics proposal documents this aspect in clear and unambiguous terms:

- Almost any class should be able to create a nothrow move assignment operator.

- a basic requirement is that a class must have a valid resource less state (i.e., remain in a valid state after having been moved)

- those that can't, shouldn't define move semantics.
by tommica | 2026-01-12 07:25:37+00:00
> They don't trust me or the logic and so dismiss it.

This is me, the logic of Monty Hall Doors does not make sense to me, so luckily I found this one: https://www.rossmanchance.com/applets/2021/montyhall/Monty.h...

After running the process 500 times, the ratio seems insane (using the stay tactic, 67% loss & 33% wins) - it makes me able to accept "that is just how it is then", but absolutely does not explain WHY, because in my mind, once you open the door, the situation resets to 50/50 - so there should be no difference if I stay or switch. The fundamental misunderstanding of statistics is probably what is the problem.

It's funny to observe own mind in this process, and how much of a "struggle" there is to convince one-self that what seems logical and sensible is in-fact a wrong interpretation and can only exists due to lack of understanding.

> My interpretation is that, before playing the actual game, they refuse to believe me. They don't trust me or the logic and so dismiss it. Once actual stakes are involved, even if it's their pride, only then do they start to be open to arguments as to why their intuition was wrong.

That is so true - before the own idea/concept gets put to test, it's easy to be delusional about how correct your own "idea" is. As long as it is in the vacuum of your own brain, you can keep it protected and shielded from all that nasty truth that tries to bully and beat it.

There is a reason why a lot of coders do not want others to see their code and do a code review on it...
by iamcalledrob | 2026-01-12 07:25:44+00:00
Surprisingly, this is an issue on Windows and Linux too -- macOS has just joined the sad party.

The location of the drag region is either the 10px-or-so just outside the window (GTK apps), or just inside the window (I see this in Electron apps). On GNOME, anyway.

On Windows this is caused by the removal of the thick window border with Win10. It wasn't really removed, it was just made transparent instead, thus the drag region moved outside the visible window to avoid the content size changing (for backwards compatibility). Apps often end up in a broken state too, because if you eschew system decoration, you lose the invisible border (which you don't even know you have), and it's easy to end up with a 1px drag region.

It's infuriating, because of the issue the author highlights -- you try and grab the window corner and fail.

It's a sad state of affairs, and a great example of how the basics are going backwards on desktop.
by noormoha | 2026-01-12 07:26:57+00:00
Hey HNI users!
I built RespCode because I was frustrated with the "one model, one answer" approach to AI coding assistants. When you're building production systems, blindly trusting a single AI's output is risky. What if it hallucinated? What if there's a better approach?

RespCode puts you back in control with 3 orchestration modes:

Compete Mode — Send your prompt to Claude, GPT-4o, DeepSeek, and Gemini simultaneously. See all 4 solutions side-by-side, compare approaches, and pick the winner. You're the judge.

Collaborate Mode — Chain models together in a refinement pipeline. DeepSeek drafts → Claude refines → GPT-4o polishes. Each model improves on the last, with full visibility into every stage.

Consensus Mode — All models generate independently, then Claude synthesizes the best parts into a merged solution. Democratic code generation.

But here's what makes it actually useful:
Every piece of generated code runs instantly in real sandboxes — not simulated, not mocked. We support x86_64, ARM64, RISC-V, and ARM32 architectures. You see compilation output, runtime results, and exit codes in seconds.

Why "Human in the Loop" matters:
AI models are powerful but imperfect. RespCode doesn't hide this — it exposes it. When you see GPT-4o produce clean code while Gemini's version has a bug, you learn which models excel at what. When Collaborate mode shows how Claude fixed DeepSeek's edge case, you understand the refinement process.

You're not just accepting AI output. You're supervising, comparing, and deciding.
This is how I believe AI development tools should work — transparent, multi-perspective, and always keeping humans in the decision seat.

Here a detailed blog on why this could solve your coding problem - https://respcode.com/blog/why-single-model-ai-assistants-hol...
Would love your feedback!
by MORPHOICES | 2026-01-12 07:27:10+00:00
In the past year, I have begun self-hosting more and more things. ~

It’s not like I enjoy running servers. I kept facing the same challenges with hosted tools - their prices increased, features changed every now and then, dashboards became noisier and simple tasks grew complicated.

What surprised me is how effectively boring self-hosting has become, and I mean that in a good way. Inexpensive equipment. Good default settings. Not as many sharp edges as I remembered.

This is the mental model that helped me.

Growth-oriented, not long-term stable, hosted tools.

Improving predictability and ownership with self-hosting.

It's not the setup cost that matters but the ongoing effort.

As services decrease, decisions also decline.

Practical choices made everything work for me.

Pick boring software with smaller feature sets.

Offer fewer services than you think you need.

Upgrades are optional not mandatory.

Settle for Acceptable UX to Maintain Control

It's not against the cloud, but… I still tons of hosted services. But I tend to be more judicious these days as to who is worthy of being depended on.

I'm keen to know how other people see this.

Have you been opting for self-hosting to a greater extent than a few years ago?

What pushed you there (cost, trust, complexity)?

What types of websites do you think are not worth self-hosting at all?

What caused it to fail if you tried?
by Sateeshm | 2026-01-12 07:27:31+00:00
> The exact time that many programmers were enlightened about the AI capabilities and the frequency of their posts.

I attribute that to the holidays. Many people finally had the time to goof around with these tools. At least that's how it happened to me.

It was an incredible experience. I implemented a few features quickly and in a much better way than I could otherwise. Realized how many tiny holes my app had and a few suboptimal patterns I was using. Made me worry about my career, initially, but after using for a while, I now see it as going up the chain of abstraction. Only thing I'm not doing is writing code by hand. Im still having to do everything else like thinking about architecture and the big picture, keeping it dry and maintainable, debugging, etc - but with a lot of help from LLMs. Sometimes it's 10x and sometimes you wasted sometime, you know, just like how using packages made us go up the chain.
by dpark | 2026-01-12 07:28:30+00:00
It’s from Working Effectively with Legacy Code. I don’t recall the exact definition but it’s something to that effect. Legacy = lack of automated tests.

The biggest barrier to changing code is usually insufficient automated testing. People are terrified of changing code when they can’t verify the results before breaking production.

More glibly legacy code is “any code I don’t want to deal with”. I’ve seen code written 1 year prior officially declared “legacy” because new coding standards were being put in place and no one wanted to update the old code to match.
by mellosouls | 2026-01-12 07:30:08+00:00
Your precedence note is fair but it seems likely the whole "ancient aliens" subject was in the air around that time; pseudohistory has existed as long as history and this particular strand just emerges with the sci-fi boom and particularly the post-war fascination with UFOs.

Von Daniken was obviously just particularly good at pushing his brand of the nonsense; all of those authors though are interesting examples of the sort of anti-academic and conspiracy theorists that have reached their apogee in recent years via social media.
by noormoha | 2026-01-12 07:30:23+00:00
I built RespCode because I was frustrated with the "one model, one answer" approach to AI coding assistants. When you're building production systems, blindly trusting a single AI's output is risky. What if it hallucinated? What if there's a better approach?

RespCode puts you back in control with 3 orchestration modes:

Compete Mode — Send your prompt to Claude, GPT-4o, DeepSeek, and Gemini simultaneously. See all 4 solutions side-by-side, compare approaches, and pick the winner. You're the judge.

Collaborate Mode — Chain models together in a refinement pipeline. DeepSeek drafts → Claude refines → GPT-4o polishes. Each model improves on the last, with full visibility into every stage.

Consensus Mode — All models generate independently, then Claude synthesizes the best parts into a merged solution. Democratic code generation.

But here's what makes it actually useful:
Every piece of generated code runs instantly in real sandboxes — not simulated, not mocked. We support x86_64, ARM64, RISC-V, and ARM32 architectures. You see compilation output, runtime results, and exit codes in seconds.

Why "Human in the Loop" matters:
AI models are powerful but imperfect. RespCode doesn't hide this — it exposes it. When you see GPT-4o produce clean code while Gemini's version has a bug, you learn which models excel at what. When Collaborate mode shows how Claude fixed DeepSeek's edge case, you understand the refinement process.

You're not just accepting AI output. You're supervising, comparing, and deciding.
This is how I believe AI development tools should work — transparent, multi-perspective, and always keeping humans in the decision seat.

Here a detailed blog on why this could solve your coding problem - https://respcode.com/blog/why-single-model-ai-assistants-hol...
Would love your feedback!
by Amlal | 2026-01-12 07:30:37+00:00
NeKernel is a microkernel project written in modern C++.
I just shipped a new release, v0.1.21, with improved APIs and a new WiP language frontend in Nectar's repository.
The following link points to the NeKernel software distribution and its development branch, please give it a star here: https://github.com/nekernel-org/src
Tell HN: Auto-download in Apple Podcasts is so unreliable it's basically useless
by garyfirestorm | 2026-01-12 07:30:48+00:00
Hop on an international flight, remember you had set automatic downloads for your favorite podcast show. Open the app to find the latest (or even last few) episodes are not downloaded.
Why is it so hard to auto download podcasts when the phone is charging at night and connected to a WiFi? What’s the point of auto-download button?
by elitan | 2026-01-12 07:32:02+00:00
Building Frost, a simple self-hosted deployment platform. Docker-only, single-user, no Kubernetes. You point it at a repo or image, it handles the build → health check → deploy → stop old container flow.

Stack: Bun, Next.js, SQLite, Kysely. Been building it almost entirely with Claude Code which has been a surprisingly effective workflow for this kind of infra tooling.

https://github.com/elitan/frost
by Manuel_D | 2026-01-12 07:32:52+00:00
Remember those systems are non-intermittent and have lifespans of 50 years or more. Server farms are not amenable to load shifting, they expect round the clock power. Trying to power them with intermittent sources would need very hefty power banks.

If this nuclear plant has 2 GW of power output, were talking about 2.4 billion dollars to store 12 hours worth of the plant's output assuming $100 per KWh of storage.