MurphyA/hacker-news huggingface dataset:
by hedayet | 2026-03-10 18:50:55+00:00
Acquisition headlines can be some of the most misleading signals in the startup ecosystem, especially acqui-hires masquerading as acquisitions.

The posted price rarely reflects what founders actually receive after dilution, investor preferences, and stock vesting are factored in.

If you’re a founder, don’t let the acquisition narrative distract you from building a durable business.
by red-iron-pine | 2026-03-10 18:51:13+00:00
a solid number of propaganda ("marketing") and malware gangs operated out of Ukraine, or other parts of Eastern Europe.

the war definitely changed those flows and targets; e.g. they now flood reddit with pro-Ukranian posts.

most of Russian agit-prop now flows out of "marketing" contractors in India, Pakistan, or Nigeria.
by ftkftk | 2026-03-10 18:51:32+00:00
I prefer Dan Shapiro's 5 level analogy (based on car autonomy levels) because it makes for a cleaner maturity model when discussing with people who are not as deeply immersed in the current state of the art. But there are some good overall insights in this piece, and there are enough breadcrumbs to lead to further exploration, which I appreciate. I think levels 3 and 4 should be collapsed, and the real magic starts to happen after combining 5 and 6; maybe they should be merged as well.
by pixl97 | 2026-03-10 18:51:56+00:00
>isn't significantly better than it was 3 years ago.

Eh?

Ever hear the saying the first 90% of a problem is 90% of the work, the last 10% of the program is also 90% of the work.

AI/LLMs have improved massively in that context. That's not even including the other model types such as visual/motion-visual/audio which are to the point that telling their output from reality is a chore.

And one shotting a simple script simply doesn't mean much without context. I have it dump relatively complex powershell scripts often enough and it's helped me a lot with being able to explain scripting actions to other humans where before I'd make assumptions about the other users knowledge where it was not warranted.
by taint69 | 2026-03-10 18:51:59+00:00
Never made it as a wise man
I couldn't cut it as a poor man stealing
Tired of livin' like a blind man
I'm sick of sight without a sense of feeling
And this is how you remind me

This is how you remind me of what I really am
This is how you remind me of what I really am

It's not like you to say sorry
I was waitin' on a different story
This time I'm mistaken
For handing you a heart worth breakin'
And I've been wrong, I've been down
Been to the bottom of every bottle
These five words in my head
Scream, "Are we havin' fun yet?"

Yet, yet, yet, no, no
Yet, yet, yet, no, no

It's not like you didn't know that
I said, "I love you," and I swear I still do
And it must have been so bad
'Cause livin' with me must have damn near killed you

And this is how you remind me of what I really am
This is how you remind me of what I really am

It's not like you to say sorry
I was waitin' on a different story
This time I'm mistaken
For handing you a heart worth breakin'
And I've been wrong, I've been down
Been to the bottom of every bottle
These five words in my head
Scream, "Are we havin' fun yet?"

Yet, yet, yet, no, no
Yet, yet, yet, no, no
Yet, yet, yet, no, no
Yet, yet, yet, no, no

Never made it as a wise man
I couldn't cut it as a poor man stealin'
And this is how you remind me
This is how you remind me

This is how you remind me of what I really am
This is how you remind me of what I really am

It's not like you to say sorry
I was waitin' on a different story
This time I'm mistaken
For handing you a heart worth breakin'
And I've been wrong, I've been down
Been to the bottom of every bottle
These five words in my head
Scream, "Are we havin' fun yet?"

Yet, yet, are we havin' fun yet?
Yet, yet, are we havin' fun yet?
Yeah, yeah (These five words in my head scream)
Are we havin' fun yet?
Yeah, yeah (These five words in my head)
No, no
by opan | 2026-03-10 18:52:01+00:00
>All the other lines set options to their default value, which is pointless.

I kinda like doing this for some programs, both as a way to see the current settings at a glance, and to avoid issues if defaults change in an update. At least twice mpv has changed default behavior and ruined my day. Once when they made scrolling vertically change volume instead of seeking (trying to match VLC?), and once when they disabled subtitles if the language matched the audio. Both easy to fix in the config file, both cases where I liked the default until they changed it.
Show HN: Modulus – Cross-repository knowledge orchestration for coding agents
by dasubhajit | 2026-03-10 18:52:03+00:00
Hello HN, we're Jeet and Husain from Modulus (https://modulus.so) - a desktop app that lets you run multiple coding agents with shared project memory.
We built it to solve two problems we kept running into:

- Cross-repo context is broken. When working across multiple repositories, agents don't understand dependencies between them. Even if we open two repos in separate Cursor windows, we still have to manually explain the backend API schema while making changes in the frontend repo.

- Agents lose context. Switching between coding agents often means losing context and repeating the same instructions again.

Modulus shares memory across agents and repositories so they can understand your entire system.

It's an alternative to tools like Conductor for orchestrating AI coding agents to build product, but we focused specifically on multi-repo workflows (e.g., backend repo + client repo + shared library repo + AI agents repo). We built our own Memory and Context Engine from the ground up specifically for coding agents.

Why build another agent orchestration tool? It came from our own problem. While working on our last startup, Husain and I were working across two different repositories. Working across repos meant manually pasting API schemas between Cursor windows — telling the frontend agent what the backend API looked like again and again. So we built a small context engine to share knowledge across repos and hooked it up to Cursor via MCP. This later became Modulus.

Soon, Modulus will allow teams to share knowledge with others to improve their workflows with AI coding agents - enabling team collaboration in the era of AI coding. Our API will allow developers to switch between coding agents or IDEs without losing any context.

If you wanna see a quick demo before trying out, here is our launch post - https://x.com/subhajitsh/status/2024202076293841208

We'd greatly appreciate any feedback you have and hope you get the chance to try out Modulus.
Show HN: G0 – The control layer for AI agents (scan, test, monitor, comply)
by debug-0101 | 2026-03-10 18:52:44+00:00
AI agents are shipping fast (LangChain, CrewAI, MCP servers, OpenAI Agents SDK) but there's no unified way to secure and govern them. We built g0 to be
that control layer.

What g0 does across the agent lifecycle:

g0 scan - Static + behavioral analysis of agent code. 1,180 rules across 12 security domains, 10 frameworks (LangChain, CrewAI, MCP, OpenAI, Vercel AI,
Bedrock, AutoGen, LangChain4j, Spring AI, Go AI), 5 languages. Detects toxic tool chains, taint flows, overprivileged descriptions, missing
sandboxing. Integrated threat intelligence checks tool URLs and dependencies against 55+ IOCs and known CVEs.

g0 test - Dynamic adversarial red teaming. Fires prompt injections, data exfiltration attempts, tool abuse sequences, jailbreaks, and goal hijacking
payloads at your running agents. 3-level progressive judge (deterministic, heuristic, LLM). Works over HTTP and MCP.

g0 endpoint - Discovers every AI tool on the machine (Claude Code, Cursor, Windsurf, Zed, 15+ tools), inventories MCP servers, and surfaces
misconfigurations. Think nmap but for your AI developer surface.

g0 daemon - Continuous runtime monitoring. Behavioral baselines with anomaly detection, cost circuit breaker, correlation engine linking events across
sources into attack chains, and a kill switch for when things go sideways.

g0 detect - MDM enrollment detection (Jamf, Intune, Mosyle, Kandji, etc.), running AI agent discovery, and host hardening audit in one view.

First-class OpenClaw support. g0 is the only security tool that understands OpenClaw's architecture: gateway hardening (18 probes),
SKILL.md/SOUL.md/MEMORY.md analysis, cognitive drift monitoring via SHA-256 baselines, deployment audits, config hardening, and ClawSec CVE feed
integration. If you're running OpenClaw in production, g0 catches what generic scanners miss.

Compliance built in, not bolted on. Every finding maps to 10 standards: OWASP Agentic Top 10, OWASP LLM Top 10, NIST AI RMF, ISO 42001, EU AI Act,
MITRE ATLAS, and more. Generate evidence records, compliance reports, and enforce policies via .g0-policy.yaml with CI gate support.

Outputs: Terminal, JSON, SARIF 2.1.0, HTML, CycloneDX AI-BOM, Markdown. Plugs into GitHub Actions, GitLab CI, or any pipeline.

One command to start: npx @guard0/g0 scan .

GitHub: https://github.com/guard0-ai/g0

We think the AI agent ecosystem needs the same security tooling maturity that web apps got with Burp Suite and Semgrep, but purpose-built for agents.
Happy to answer questions about the architecture or threat model.
by john_strinlai | 2026-03-10 18:52:49+00:00
hi dang. while you are here -- are comments artificially ordered on this post?

https://news.ycombinator.com/item?id=47326953 is grey (i.e <=0 karma). my top-level comment is at 14 karma. we posted within 15 minutes of each other. ive never seen something like that before.

the two posts calling out unethical behavior have been living at the bottom of this post the entire time, until a couple of actually [flagged] comments ended up under them.

(edit: 15 karma now, and still lower than a 0 karma comment posted at roughly the same time)
by jfengel | 2026-03-10 18:53:00+00:00
I know you're not being serious, but "animation" and "live action with CGI" are different filmmaking styles.

They live on opposite sides of the uncanny valley. One is meant to appear completely realistic. The other is intended to be stylized, and would be ruined by being realistic.

It's one reason why live-action remakes of animated shows so rarely work. Humans can't act, move, or look like cartoons. The result is usually dull, not because anything looks wrong but because it looked so much better fully animated.

When you watch CGI superheroes, they're supposed to trick you into thinking you're watching a real thing. The filmmakers would have done it live if they could; the option simply wasn't available.
by johnnyanmac | 2026-03-10 18:53:08+00:00
If you think China is some mass surveillance state where every single yard of dissent is carpet bombed: yes, I can see why you think that way.

Just like the US, it can take a whike for thr CCP to get around to every individual. It's a large country. Your mistake is thinking that that's the line it has to get to before we can compare a country to China/Russia.
by Retric | 2026-03-10 18:53:15+00:00
Wordle involved actually selling the rights to something not just allowing AI to be trained on it while he kept the website.

That’s really not a reasonable comparison to what is being sought.

As to global artists, I was suggesting the majority of artists globally make ~20k USD per year. Double it and 6 months salary is still only 20k and would be seriously tempting offer when you retain all rights to past and future works.
by eikenberry | 2026-03-10 18:53:27+00:00
Prepaid cards can't masquerade as credit cards as there are easy ways to differentiate them (the numbers have meaning) and a minor getting access to the family credit card is the parents giving them permission. I'm not convinced credit card for age verification is a good solution for all cases but for cases where you've already used a credit card to access the service it would be perfect.
by sothatsit | 2026-03-10 18:54:12+00:00
RL on LLMs has changed things. LLMs are not stuck in continuation predicting territory any more.

Models build up this big knowledge base by predicting continuations. But then their RL stage gives rewards for completing problems successfully. This requires learning and generalisation to do well, and indeed RL marked a turning point in LLM performance.

A year after RL was made to work, LLMs can now operate in agent harnesses over 100s of tool calls to complete non-trivial tasks. They can recover from their own mistakes. They can write 1000s of lines of code that works. RL seems to have broken LLMs out into a similar learning territory as you describe.
by vasanthgeethanr | 2026-03-10 18:54:51+00:00
Location: San Francisco, CA
Remote: Optional; remote or in-office ok
Willing to relocate: Yes (US)
Technologies: React, JavaScript, TypeScript, Python, Tailwind, Angular, HTML/CSS, Vite, Java, SQL, Node.js, Mongo
Resume: https://www.linkedin.com/in/vasanthgeethanraju/
Email: vasanthgeethan.raju@gmail.com

Software Engineer with 7+ years of experience building scalable, customer-focused products. I thrive in rapidly evolving
environments where I take ownership, turn complex problems into clear solutions, and ship software that meaningfully improves
people’s lives. Grounded in full-stack and automation experience, I build with a deep respect for quality, reliability, and long-term
impact of the product for customers.
by SllX | 2026-03-10 18:54:52+00:00
> That's a false dichotomy. The alternatives includes giving each country an equal standing without a veto, votes proportional to the population, or even fully direct democracy by every person in the world, and a million other alternatives I could think of if given an afternoon.

These are certainly alternatives but they would take what’s basically an acceptable-ish arrangement and turn it into what’s effectively a world government, and that’s completely untenable.

If liberal secular democracies that respected free speech and private property rights were the order of the day, we might be able to set something like that up, but not in today’s world with today’s leaders, and the UN has to account for all of those differences. That’s why the UN feels unsatisfying and why it will never “lead” the world.
by Mooshux | 2026-03-10 18:55:01+00:00
The plaintext storage problem is real, but migrating to a secrets manager still leaves agents carrying long-lived tokens they don't need. Even if the key isn't in a config file, the agent has it in memory for the duration of the session.

The pattern that actually closes the gap: issue short-lived scoped tokens at request time, never hand the real key to the agent at all. The agent gets a proxy credential that expires after the session. If it leaks, it's already stale. We wrote up the full implementation here: https://apistronghold.com/blog/phantom-token-pattern-product...
by abraxas | 2026-03-10 18:55:16+00:00
Which in turn were only invented because millennials would not be caught dead writing Java and JSP. We had all this shit figured out by the late nineties and 90% of what is accomplished on the web today was entirely possible and well integrated in Java app servers.

This whole business is a fashion industry.

I'm for one grateful for LLMs because for the first time in around 30 years there is actually genuine novelty to explore in software engineering. Ruby and nodejs weren't it.
by jeffdico | 2026-03-10 18:55:16+00:00
I need help finding gigs, this year has been one of a kind. I have jobs I did last year that the client is finding it difficult to even pay for what has been done.

I am a software engineer with 12 years of experience. I put in the work and am also running my own business, and it's also tight making ends meet there.
I just want part-time or full-time freelance remote work. I always deliver on my work.

Thanks in advance...
by ntonozzi | 2026-03-10 18:55:18+00:00
Why do they need to run benchmarks to confirm performance? Can't they run an example prompt and verify they get the exact same output token probabilities for all prompts? The fact that they are not doing this makes me suspicious that they are in fact not doing the exact same thing as vLLM.

It is also a bit weird that they are not incorporating speculative decoding, that seems like a critical performance optimization, especially for decode heavy workloads.
by aleksiy123 | 2026-03-10 18:55:51+00:00
One topic of llms not doing well with UI and visuals.

I've been trying a new approach I call CLI first.

Essentially instead of trying to get llm to generate a fully functioning UI app.

You focus on building a local CLI tool first.

It can directly call the CLI tool and you can iterate on the design of whatever you are building quickly.

You can get it to walk through the flows, and journeys using the CLI prototype and iterate on it quickly.

Your commands structure will very roughly map to your resources or pages.

Once you are satisfied with the capability of the cli tool. (Which may actually be enough, or just local ui)

You can get it to build the remote storage, then the apis, finally the frontend.

All the while you can still tell it to use the cli to test through the flows and journeys, against real tasks that you have, and iterate on it.

I did recently for pulling some of my personal financial data and reporting it. And now I'm doing this for another TTS automation I've wanted for a while.
by voxleone | 2026-03-10 18:55:54+00:00
In the 90s people hoped Unified Modeling Language diagrams would generate software automatically. That mostly didn’t happen. But large language models might actually be the realization of that old dream. Instead of formal diagrams, we describe the system in natural language and the model produces the code. It reminds me of the old debates around visual web tools vs hand-written HTML. There seems to be a recurring pattern: every step up the abstraction ladder creates tension between people who prefer the new layer and those who want to stay closer to the underlying mechanics.

Roughly: machine code --> assembly --> C --> high-level languages --> frameworks --> visual tools --> LLM-assisted coding. Most of those transitions were controversial at the time, but in retrospect they mostly expanded the toolbox rather than replacing the lower layers.

One workflow I’ve found useful with LLMs is to treat them more like a code generator after the design phase. I first define the constraints, objects, actors, and flows of the system, then use structured prompts to generate or refine pieces of the implementation.
by the_af | 2026-03-10 18:55:56+00:00
According to this theory, the Clueless are the ones who suffer the most.

They invest most, they care about made up goals nobody else cares about, they play by rules everyone else thinks are dumb, they feel loyal to a company that doesn't love them back, and because they are more invested in the company, they are the ones who feel the loss the most when the sociopaths pull the rug.

I think it's actually the Losers who have it better: they are simply not invested enough, they are replaceable but also find their place in other companies, and in any case, failure affects us-- I mean, them -- less simply because they are not invested as much and they never felt any loyalty.

"Loser" is a loaded term because it sounds like the cultural, lowercase loser ("so and so is such a loser!") but it actually means "loser in the game of maximum capitalist profit and power". But if you're not really playing that game, being a loser at it isn't so bad.
by ralferoo | 2026-03-10 18:56:04+00:00
It's not really hinted at in the article, which doesn't actually mention whether the rewrite was a net gain - I presume it was or they wouldn't have written the article, and the lead-in picture paints a rosy picture, but the tone at the end suggests he's not happy with how things turned out.

But one thing that used to be a common design anti-pattern was the "version 2 problem". I think I first heard about it when Netscape were talking about how NN2 was a disaster, and they were finally happy with NN3 or NN4.

Often version 1 is a hastily thrown together mess of stuff, but it works and people like it. But there's lots of bad design decisions and you reach a limit with how far you can continue pushing that bad design before it gets too brittle to change. So you start on version 2, a complete rewrite to fix all the problems and you end up with something that's "technically perfect" but so overengineered, it's slow and everybody hates it, plus there are probably lots of workflow hoops to jump through to get things approved that you end up not making any progress, and possibly version 2 kills the product and/or the company.

The idea is that the "version 3" is a pragmatic compromise - the worse design problems from version 1 are gone, but you forego all the unnecessary stuff that you added in version 2, and finally have a product that customers like again (assuming you can convince them to come back and try v3 out) and you can build into future versions.

To a large degree I think this "version 2 problem" was a by product of waterfall design, it's certainly been less common since agile development became popular in the early 2000s and tooling made large scale refactoring easier, but even so I remember working somewhere with a v1 that the customers were using and a v2 that was a 3-year rewrite going on in parallel. None of the developers wanted to work on v1 even though that's what brought in the revenue, and v2 didn't have any of the benefit of the bug fixes accumulated over the years to fix very specific issues that were never captured in any of the scope documents.
by opan | 2026-03-10 18:56:19+00:00
Codeberg has my favorite UI of the bunch as well. As a regular user rather than a programmer, I really appreciate how easy it is to find both Issues (I am a frequent bug reporter) and Releases near the top of the page. GitHub hides Releases on the side or bottom (mobile), and GitLab's UI is such a mess I don't even know where to start. I've often edited my URL to get to Issues or Releases on some git forges because it's easier than dealing with their UI.
by lich_king | 2026-03-10 18:56:26+00:00
> The Wason selection task is the classic example: most people fail a simple conditional reasoning problem unless it’s dressed up in familiar social context, like catching cheaters.

I've never heard about the Wason selection task, looked it up, and could tell the right answer right away. But I can also tell you why: because I have some familiarity with formal logic and can, in your words, pattern-match the gotcha that "if x then y" is distinct from "if not x then not y" and "y if and only if x".

In contrast to you, this doesn't make me believe that people are bad at logic or don't really think. It tells me that people are unfamiliar with "gotcha" formalities introduced by logicians that don't match the everyday use of language. If you added a simple additional to the problem, such as "Note that in this context, 'if' only means that...", most people would almost certainly answer it correctly.

Mind you, I'm not arguing that human thinking is somehow more profound from what what LLMs can do. However, judging from the output, LLMs have a tenuous grasp on reality, so I don't think that reductionist arguments along the lines of "humans are just as dumb" are fair.
by worik | 2026-03-10 18:56:35+00:00
I simply used Emacs for 25 years, avoiding editing .emacs entirely

Only in the past years have I started customizing it

My attraction to Emacs is stability and I can use it in text or GUI mode.

Many editors have come and gone in that time, many employers insist I use this or that piece of over designed, under done GUI. When I have the chance, back to Emacs