MurphyA/hacker-news huggingface dataset:
by autoexec | 2026-02-18 05:58:56+00:00
I've seen it said plenty of the times that the code might work eventually (after several cycles of prompting and testing), but even then the code you get might not be something you'd want to maintain, and it might contain bugs and security issues that don't (at least initially) seem to impact its ability to do whatever it was written to do but which could cause problems later.
by transcriptase | 2026-02-18 05:59:44+00:00
Mentioning AI in an earnings call means fuck all when what they’re actually referring to is toggling on the permissions for borderline useless copilot features across their enterprise 365 deployments or being convinced to buy some tool that’s actually just a wrapper around API calls to a cheap/outdated OpenAI model with a hidden system prompt.

Yeah, if your Fortune 500 workplace is claiming to be leveraging AI because it has a few dozen relatively tech illiterate employees using it to write their em dash/emoji riddled emails about wellness sessions and teams invites for trivia events… there’s not going to be a noticeable uptick in productivity.

The real productivity comes from tooling that no sufficiently risk adverse pubco IS department is going to let their employees use, because when all of their incentives point to saying no to installing anything ever, the idea of giving the permissions required for agentic AI to do anything useful is a non-starter.
by sylwester | 2026-02-18 06:00:35+00:00
I built TinyIce as a vibing side project to spin up an Icecast2-compatible server in seconds, because I was frustrated with IceCast. One static Go binary, embedded assets, auto-generated creds on first run, built-in ACME (Let’s Encrypt), relays, multi-tenant admins, Prometheus metrics, and a modern web UI.
by gpt5 | 2026-02-18 06:00:40+00:00
SpaceX is making that majority (70%) of its revenue, and all of its profits from Starlink, and mostly from subscriptions.

98% of government money SpaceX receives is payment for services rendered, which they provide at a significantly lower cost than their competitors.

On the other hand, their competitors are routinely receiving actual handouts. For example, ULA used to receive a $1 billion annual "Launch Capability" stipend essentially just to keep their lights.
by Haven880 | 2026-02-18 06:01:57+00:00
Russia sells wheat too. Minerals too. Weapons. You will be surprised the oil part isnt at 100% as what western media is telling you. Plus this source is mostly based on what western finance can see. BRICS dont submit data to westrrn finance analysyst anymore since 3 years ago. Anything you want to buy stock or trade you must absolutely ignore western hypes. Incredibly unreliable.
by walterbell | 2026-02-18 06:02:17+00:00
Carl Ledbetter interview (2024), https://www.youtube.com/watch?v=kS-k8p0dbB4

Carl was a Technical Consultant across all four seasons of Halt and Catch Fire, providing industry insight and script review. Hear what he had to say about his experience on the show, a breakdown of specific scenes, and some of his favorite memories.
by mrtksn | 2026-02-18 06:02:23+00:00
Do you think that it is a good idea to release it first on iOS, announce on HN and Producthunt? How would you do?

On my app the tech is based on running agent generated code on JavaScriptCore to do things like OpenClaw, I’m wrapping the JS engine with the missing functionality like networking, file access and database access so I believe I will not have a problem with releasing it on Apple AppStore as I use their native stack. Then since this stack is also OS, I’m making a version that will run on Linux, the idea being users develops their solution on their device(iOS&Mac currently) see it working and and then deploys on a server with a tap of a button, so it keeps running.
by CTDOCodebases | 2026-02-18 06:02:50+00:00
Judging by the news isn’t the pivot to creating autonomous driving systems for other manufacturers cars?

If I’m understanding correctly the pivot is to sell just the autonomous driving systems. This way it can be trained on more data. It’s a hard sell to do this while competing against the car makers whose business they are trying to court.

Selling actual cars was like Uber when they started with a black car service. Get into the luxury market then leverage that so get into the mass market.

Perhaps this is why Elon has been so adamant about not using LiDAR
by shubhamjain | 2026-02-18 06:03:24+00:00
The mystery I can wrap my head around is how Tesla has avoided getting hammered despite being hit from a hundred different directions. What exactly is the market pricing in?

They peaked around 2021, and even after posting multiple quarters of disappointing results, the stock is still trading above 2021 levels. For almost any other company, slightly lowering guidance or missing estimates by a few percentage points simply tanks the stock. But for Tesla, no amount of Musk’s idiocy seems to be enough to seriously move it.
by Haven880 | 2026-02-18 06:04:07+00:00
Russia will win on this one. Productions are largely internal. What they lack they get from China. Ukraine loss so many men. Their populations will just go down from now on. USA and China are on the verge of recessions. I really doubt USA will prioritize Ukraine over Israel or China ignoring its own needs. Cede the land and rebuilt. Better to cut losses now than even more loss.
by forgetfreeman | 2026-02-18 06:05:39+00:00
Actually if you run the tape back Tesla spent over a decade on trivially preventable manufacturing fuckups by attempting to ignore a century of industry knowledge on the subject and just wing it silicon valley style. That they have infrastructure that is capable of performing manufacturing at some scale is not in question. That any of it is sufficiently optimized for sanity to be repurposed remains to be seen.
by 1broseidon | 2026-02-18 06:05:59+00:00
I think it’s kinda one of those YMMV metrics. I work for a large company around 80-100k employees and they are ranked on this list. The business unit I’m in is amazing and I truly feel that it’s a great place to work. But ask someone in a dying business unit how they feel and they’ll say they’re overworked and understaffed.
Show HN: TokenMeter – Open-source observability layer for LLM token costs
by Mohit8880 | 2026-02-18 06:07:52+00:00
Hi HN,

I built TokenMeter after seeing how unpredictable LLM costs become as usage scales.

Most teams optimize prompts but lack real-time cost observability.

This project tracks token usage and exposes cost insights to help AI teams stay financially aware.

Would appreciate feedback on architecture and missing observability features.

Thanks.
by alephnerd | 2026-02-18 06:08:03+00:00
Who's your persona? How are you pricing and packaging? Who is your buyer? Are you D2C? Consumer? Replacing EAs? Replacing Project Managers? ...

You need to answer these questions in order to decide whether a Show HN makes sense versus a much more targeted launch.

If you do not know how to answer these questions you need to find a cofounder asap. Technology is commodified. GTM, sales, and packaging is what turns technology into products. Building and selling and fundraising as 1 person is a one-way ticket to burnout, which only makes you and your product less attractive.

I also highly recommend chatting with your network to understand common types of problems. Once you've identified a couple classes of problems and personas for whom your story resonates, then you can decide what approach to take.

Best of luck!
Anthropic's pricing wall is routing enterprise revenue to OpenAI
by luckygreen | 2026-02-18 06:08:49+00:00
I've spent the last week trying to use Claude Opus in an IDE via a localhost proxy that wraps the Claude Code CLI.

The proxy exists because there's no way to get programmatic API access to Claude on a Pro ($20/mo) or Max ($200/mo) subscription.

This isn't an oversight. Anthropic has actively taken steps to prevent subscription-based API access. They've shut down third-party bridges, tightened terms of service, and made it clear this is corporate policy, not neglect, not a missing feature, but a deliberate business decision.

Meanwhile, OpenAI opened API access to ChatGPT Pro/Plus subscribers. The result is predictable.

A CTO friend is prototyping an electronic warfare detection system. His existing customers include a major European MNO that operates across dozens of countries. He's currently splitting ~$80/month across four AI subscriptions, constantly rationing tokens, juggling providers. He'd switch to Claude Max tomorrow if it included IDE API access. Instead, he's moving his entire prototype to Codex/OpenAI, because they made it possible.

Here's why this matters beyond one developer: The prototype becomes the demo. The demo becomes the procurement spec. The spec becomes a multi-year enterprise contract. This particular MNO signs seven-figure deals per country rollout. Once the prototype is built on OpenAI, Claude never enters the conversation. Anthropic doesn't just lose one deal, they lose an entire multi-country enterprise pipeline they'll never even know existed.

This isn't an isolated case. In my circle, senior engineers, CTOs, infrastructure people, nearly everyone would switch from Pro to Max if it meant using Claude in their IDE the way they can now use OpenAI. That's going from $20/month to $200/month per user, zero acquisition cost. Even if only 10-20% of the broader Pro base converts, the revenue math is overwhelming.

The proxy ecosystem (claude-max-api-proxy, Antigravity, and others) is direct proof of unmet demand. Developers are writing code to work around a billing boundary. That's not abuse, that's a market signal Anthropic is choosing to ignore.

Claude Opus is technically superior to Codex for most development tasks. That means nothing when developers can't access it in their workflow.

Anthropic built the best model and then made a policy decision to keep it out of the environment where long-term platform adoption is decided.
by Twisell | 2026-02-18 06:09:12+00:00
Unless I misunderstood your workflow Forgejo Agit approach mentioned in OP might already cover that.

You can push any ref not necessarily HEAD. So as long as you send commit in order from a rebase on main it should be ok unless I got something wrong from the doc?

https://forgejo.org/docs/latest/user/agit-support/
by Mohit8880 | 2026-02-18 06:09:37+00:00
Hi HN,

I built TokenMeter after noticing how unpredictable LLM token costs become once usage scales.

Most teams optimize prompts, but few track real-time financial exposure at the token level.

This project attempts to provide a lightweight observability layer focused on cost transparency.

Would appreciate feedback on architecture and missing infra-level features.

Thanks.
by realusername | 2026-02-18 06:10:00+00:00
> You don't need the OS providing anything to use arbitrarily modified APKs. We also don't want to give apps a legitimate reason to ban GrapheneOS as opposed to being able to convince the tiny number of apps enforcing Google certification to allow it.

I think you said the truth out loud, a rom which tries too much to fight for your privacy would just be banned. (And I do agree with that)
by bhu8 | 2026-02-18 06:10:09+00:00
This is amazing. I checked some games and the blunders make me think that the LLMs are not really great at forecasting what happens if they play X on Y.

Can you actually introduce that into the decision making? That is, you would:

1. Have the LLM come up with N many potential actions

2. Run XMage run in parallel and provide the outcome for each different action

3. Revert XMage to the original state

4. Provide the LLM with the different outcomes and have them choose the action/outcome pair rather than just the action

This would actually help them analyze the counterfactual outcomes more effectively and should prevent 99% of the blunders

If you happen to be token rich, you could even do this in a MCTS manner and have them think really deep
by throwaway81523 | 2026-02-18 06:10:25+00:00
This looks cool, but says it's simpler than Seastar. Seastar last time I looked at it was fairly simple, but didn't use coroutines at all. Instead it used a futures/promise scheme. It was in C++14, back when C++20 coroutines didn't exist yet.

C++20 coroutines have seemed very complex to me and I haven't sat down to try to understand them. I guess tiny_coro could help for that. I do remember that they were stackless.

I'm not that keen on coroutine and async approaches to concurrency anyway these days. I'd rather use something with actual multitasking, either with Posix threads or with lightweight processes like Erlang's or Go's.

Also, C++ itself is apparently in the process of sinking into a bog. Rust is taking over, which is not entirely good news. I had wanted to spend more time on Ada.
by keepamovin | 2026-02-18 06:10:31+00:00
This is truer than you think. It's a good selective pressure for engineers to evolve the less rational parts of their nature. And to those clutching pearls about security, reality doesn't care about your imagined fears - just what you can build. The fears to which you cling because you think it says "I'm still needed", are not real. And...were you making secure code and systems before this? You weren't. So get over yourselves, and embrace the new. Or become what you fear: redundant. Not because engineering skills were no longer important, but because you refused to develop the other things that were. The time is now.
by hn_throwaway_99 | 2026-02-18 06:11:20+00:00
The irony is that this especially true for Coca Cola. They are basically an advertising company at heart. They sell flavored sugar water. For all the hype about "are you a coke person or a Pepsi person", in blind tests most people can't tell the difference between coke and generic cola. The billions they spend in marketing annually helps ensure they can sell their flavored sugar water for a lot more than Aldi sells their store brand flavored sugar water.
by g-mork | 2026-02-18 06:12:45+00:00
this weirdly skirts my own experience yet somehow still read like sarcasm hehe. I think if we just return to calling it intelligent autocomplete expectations for productivity gain would be better established.

trying to hacksmash Claude into outputting something it simply can't just produces endless mess. or getting into a fight pointing out issues with what it's doing and it just piles on extra layer upon layer of gunk. but meanwhile if you ask it to boilerplate an entire SaaS around the hard part, it's done in about 15 seconds.

of course this says nothing about the costs of long term maintainability, and I think everyone by now recognises what that's going to look like
by oblio | 2026-02-18 06:13:08+00:00
> This pattern has already played out in chess and go. For a few years, a skilled Go player working in collaboration with a go AI could outcompete both computers and humans at go. But that era didn't last. Now computers can play Go at superhuman levels. Our skills are no longer required. I predict programming will follow the same trajectory.

Both of those are fixed, unchanging, closed, full information games. The real world is very much not that.

Though geeks absolutely like raving about go and especially chess.
by kcaseg | 2026-02-18 06:13:49+00:00
I tried Obsidian a couple of years ago when all those „Hack your brain with Obsidian“ videos were flooding YouTube, I even had a subscription.

Turns out my brain is beyond saving, while the program was pretty neat, having to have an extra window open was just beyond my attention span. Now I use a notebook, it is chaotic and has coffee strains but I actually use it.
by sujitn | 2026-02-18 06:14:08+00:00
I’ve been building LaminarDB, an embedded streaming SQL database in Rust. Define streaming SQL (tumbling/hopping/session windows, materialized views), push data in, subscribe to results. Everything in-process, no JVM, no cluster.

I come from financial systems where the options for real-time aggregation were kdb+ (expensive licensing) or Flink (JVM cluster). Many use cases just need a library.
Some technical details:

∙Three-ring architecture. Ring 0 is the hot path: mmap’d state store, zero heap allocations, no locks. Ring 1 handles async checkpointing and compaction via RocksDB. Ring 2 is the control plane. Background work never blocks data processing.

∙Thread-per-core execution. Each core gets a dedicated Tokio runtime and owns its data. No shared thread pools, no work stealing.

∙DataFusion for SQL parsing and optimization, extended with custom streaming window operators and incremental materialized view maintenance. Arrow RecordBatch is the internal format, no conversion at boundaries.

Python bindings via PyO3 + maturin with zero-copy Arrow interop for pandas, Polars, PyArrow.

Currently at v0.13.1 with pre-built binaries. Performance targets in the README are all marked “In Progress,” no published benchmarks yet.

Happy to go into detail on any of the internals.
by CamperBob2 | 2026-02-18 06:15:51+00:00
What market insight explains TSLA other than the same thing you'd hear on Reddit: that TSLA investors are a glassy-eyed, slack-jawed cult?

Are there any other explanations that can be steelmanned, just for the sake of an even-handed discussion? "We're going to build humanoid robots" just doesn't seem like enough. Neither does "We're going to build robotaxis", considering that other companies like Waymo are already well ahead of Tesla in that sector.
by transcriptase | 2026-02-18 06:16:05+00:00
It’s comical that Microsoft inserted Copilot buttons throughout all of their productivity suite, and none of them are able to do the bare minimum that you would hope for.

“Oh cool, copilot is in excel! I’m going to ask it a question about the data in the spreadsheet that it’s literally appearing beside natively in-app, or for help with a formula!”

“Wait what, it’s saying it can’t see anything or read from the currently displayed worksheet? Why is it inside the application then? Why would I want an outdated version of ChatGPT with no useful context or ability to read/do anything inside all my Office applications?”
by hn_throwaway_99 | 2026-02-18 06:16:18+00:00
This is also kinda wrong because the downside can be a lot more than your marketing spend if people really hate your ad. Just look what happened when Budweiser decided to send a personalized Bud Light can to a transgender person. For the Superbowl specifically, I can't imagine the "Search Party" ad helped Amazon sell more Rings.
by YaraDori | 2026-02-18 06:16:18+00:00
Hey HN! Creator here. OpenClaw is an open-source personal AI agent that runs 24/7 on your own hardware.

What makes it different from ChatGPT/Claude:
- It connects to your actual messaging apps (WhatsApp, Telegram, Slack, Discord, Signal)
- It has 800+ skills that do real things (control smart home, manage calendar, send emails)
- It runs on YOUR machine - your data stays local
- It can proactively reach out (reminders, alerts, monitoring)

Think of it as Jarvis but open-source. Featured in WIRED, has a Wikipedia page.

Tech stack: Node.js, works with Claude/GPT/Gemini/local models. MIT licensed.

GitHub: https://github.com/openclaw/openclaw
Docs: https://docs.openclaw.ai

Happy to answer any questions!
by autoexec | 2026-02-18 06:17:58+00:00
If nothing else AI is making great strides in surveillance. It makes mistakes, but that only matters when there's accountability, and now it can make them at scales that were unthinkable before. Most of us are not going to enjoy the new experiences AI brings us, but a small number of people are already making a lot of money selling new services to government and law enforcement.
by selcuka | 2026-02-18 06:18:11+00:00
> Suddenly, smart AI-enabled juniors can easily match the productivity of traditional (or conscientious) seniors, so why hire seniors at all?

I guess we'll see, but so far the flattening curve of LLM capabilities suggest otherwise. They are still very effective with simpler tasks, but they can't crack the hardest problems like a senior developer does.
by AnthonyMouse | 2026-02-18 06:20:15+00:00
> Tesla now has to pitch electric cars to right-wing climate-change deniers, which is not a great strategy to adopt voluntarily or otherwise.

Part of the trouble here is that was always the case. The best selling "car" in the US is the Ford F-series truck. Followed by the Chevy truck, two Japanese SUVs, the Stellantis truck, the GMC rebadge of the Chevy truck, a Chevy SUV and then the Tesla Model Y.

To get anywhere they were always going to have to appeal to the people who buy trucks.

And when everything is polarized and your product is tribe-coded, how do you do that?

I suspect the error here was buying Twitter and then aligning with the party expected to take power instead of buying Twitter and then using it to shift things in the direction of depolarization.

It also doesn't help that the Cybertruck looks weird and costs too much. I mean you can blame attitudes as you like but then there's the fact that the F-150 starts at ~$40k and the Cybertruck starts at ~$80k. They need the battery prices to come down more before people are going to buy something that needs as much battery as a truck.
by NitpickLawyer | 2026-02-18 06:21:18+00:00
> I can see the argument if you’re familiar with poetry terms,

I think they mean "if you're familiar with Anthropic's family of models". They've had the same opus > sonnet > haiku line of models for a couple of years now. It's assumed that people already know where sonnet 4.6 lands in the scheme of things. Because they've had that in 4.5, and 4.1 before it, and 4 before it, and 3.7 before it, etc.
by cyberax | 2026-02-18 06:21:28+00:00
I don't know, I can distinguish between Coca-Cola and Pepsi-Cola easily. I prefer Diet Coke, FWIW.

I also now have a bottle of Lab Cola from https://www.youtube.com/watch?v=TDkH3EbWTYc and it _is_ indistinguishable from regular Coca-Cola to me. So it might be plausible in case of a deliberate Coca-Cola knock-off?
by tabs_or_spaces | 2026-02-18 06:21:52+00:00
My experience has been

* If I don't know how to do something, llms can get me started really fast. Basically it distills the time taken to research something to a small amount.

* if I know something well, I find myself trying to guide the llm to make the best decisions. I haven't reached the state of completely letting go and trusting the llm yet, because the llm doesn't make good long term decisions

* when working alone, I see the biggest productivity boost in ai and where I can get things done.

* when working in a team, llms are not useful at all and can sometimes be a bottleneck. Not everyone uses llms the same, sharing context as a team is way harder than it should be. People don't want to collaborate. People can't communicate properly.

* so for me, solo engineers or really small teams benefit the most from llms. Larger teams and organizations will struggle because there's simply too much human overheads to overcome. This is currently matching what I'm seeing in posts these days
by johnfn | 2026-02-18 06:21:54+00:00
I have to be honest with you: I am the biggest AI booster alive, and even I would never buy a book fully written by AI. Maybe ask me again in 5 years, but I just don't think the quality is there.

That being said, I think you might be on to something with the bilingual book idea - it might be worth exploring there. But if you want to keep the AI angle, you'd have to come up with a pretty clever twist.
by upmind | 2026-02-18 06:22:31+00:00
Does he explain why he thinks OpenAI is the best way to "change the world". I really think he's wrong there. He's one person in a 3000 person organisation vs this product that has insane traction right now and has companies willing to purchase it for 8-9 digits. This feels worse for the Bun JS acquisition because you know that it likely won't be worked on seriously again by him unlike Bun.