MurphyA/hacker-news huggingface dataset:
Show HN: OmoiOS–190K lines of Python to stop babysitting AI agents (Apache 2.0)
by kanddle | 2026-03-05 16:07:21+00:00
AI coding agents generate decent code. The problem is everything around the code - checking progress, catching drift, deciding if it's actually done. I spent months trying to make autonomous agents work. The bottleneck was always me.

Attempt 1 - Claude/GPT directly: works for small stuff, but you re-explain context endlessly.

Attempt 2 - Copilot/Cursor: great autocomplete, still doing 95% of the thinking.

Attempt 3 - continuous agents: keeps working without prompting, but "no errors" doesn't mean "feature works."

Attempt 4 - parallel agents: faster wall-clock, but now you're manually reviewing even more output.

The common failure: nobody verifies whether the output satisfies the goal. That somebody was always me. So I automated that job.

OmoiOS is a spec-driven orchestration system. You describe a feature, and it:

1. Runs a multi-phase spec pipeline (Explore > Requirements > Design > Tasks) with LLM evaluators scoring each phase. Retry on failure, advance on pass. By the time agents code, requirements have machine-checkable acceptance criteria.

2. Spawns isolated cloud sandboxes per task. Your local env is untouched. Agents get ephemeral containers with full git access.

3. Validates continuously - a separate validator agent checks each task against acceptance criteria. Failures feed back for retry. No human in the loop between steps.

4. Discovers new work - validation can spawn new tasks when agents find missing edge cases. The task graph grows as agents learn.

What's hard (honest):

- Spec quality is the bottleneck. Vague spec = agents spinning.
- Validation is domain-specific. API correctness is easy. UI quality is not.
- Discovery branching can grow the task graph unexpectedly.
- Sandbox overhead adds latency per task. Worth it, but a tradeoff.
- Merging parallel branches with real conflicts is the hardest problem.
- Guardian monitoring (per-agent trajectory analysis) has rough edges still.

Stack: Python/FastAPI, PostgreSQL+pgvector, Redis (~190K lines). Next.js 15 + React Flow (~83K lines TS). Claude Agent SDK + Daytona Cloud. 686 commits since Nov 2025, built solo. Apache 2.0.

I keep coming back to the same problem: structured spec generation that produces genuinely machine-checkable acceptance criteria. Has anyone found an approach that works for non-trivial features, or is this just fundamentally hard?

GitHub: https://github.com/kivo360/OmoiOS
Live: https://omoios.dev
by PaulDavisThe1st | 2026-03-05 16:07:32+00:00
They weren't buying insurance. There's no insurance payout for the companies. They got a small amount of money in hand, and lost the chance to reclaim any of the tariff refund. That isn't insurance.

Also, the SCOTUS is not a criminal court, it is a constitutional court. If a case is heard there, both sides have not agreed on "obvious illegality". That is unsuprising since in general one side (in this case, the administrative branch of the US Government) is being accused of illegal behavior - when it comes to constitutional rather than criminal questions, most parties do not just accept their guilt, but push as far as they can towards exoneration.

Frequently, however to everybody else, the case concerns obvious illegality.
by toomuchtodo | 2026-03-05 16:07:45+00:00
https://www.politico.com/news/2026/02/27/solar-powers-newest...

https://www.pewresearch.org/2025/11/05/impact-of-climate-cha...

https://www.pewresearch.org/2025/08/19/global-climate-change...

https://www.pewresearch.org/science/2024/12/09/how-americans...

https://www.pewresearch.org/short-reads/2023/08/09/what-the-...
by mikestew | 2026-03-05 16:08:52+00:00
Utter nonsense

Got something other than anecdata? Because a web search returns a list of contrary sources as long as my arm.

But, hell, if we are trading stories, I dipped snuff for 30 years and I’ve consumed coffee since middle school. I can go days without coffee, even if I might not be happy about it. Quitting tobacco, OTOH, that was tough, with multiple starts and stops until success.
by msabalau | 2026-03-05 16:08:55+00:00
It's a bit simplistic to personify complex organizations of millions of people like "The Government" or "The Market" as if they were a living, breathing persons with a single mind.

There were people working in government who successfully attacked Oppenheimer for personal and/or policy reasons, people who stood by, and people who unsuccessfully supported him, voted to clear him, or condemned the proceedings.

Oppenheimer still paid the price, and arguably, the risks to someone like him today are considerably higher, as the current administration isn't exactly like Eisnehower's.

Nevertheless it's reductionist, reifying sentimentality to talk about "the government" turning "viciously" on someone who "served them well" because they are defying its agenda. The government isn't a character in Game of Thrones. The responsibility lies with the specific individuals who attacked him, and those who stood by.
by kanddle | 2026-03-05 16:08:55+00:00
Creator here. TL;DR: OmoiOS takes a feature description, generates structured specs with acceptance criteria, dispatches agents to isolated cloud sandboxes, validates each task autonomously, and produces a PR. You review the PR, not every intermediate step.

The core insight: AI coding tools are great at generating code, but someone still has to verify the output matches the goal. Usually that someone is you. OmoiOS automates that oversight loop.

How this compares to what you're probably using:

- vs Claude Code / Cursor: great interactive tools where you're in the loop. OmoiOS is for when you want to write the spec, approve the plan, and walk away.

- vs Codex: both produce PRs, but Codex is prompt-driven (individual tasks). OmoiOS is spec-driven (full feature lifecycle). Also open-source and not locked to one provider.

- vs Kiro: both spec-driven, but Kiro is a VS Code fork for interactive work. OmoiOS runs autonomously in the cloud. Also open-source, self-hostable, multi-model.

- vs CrewAI / LangGraph: agent frameworks (primitives). OmoiOS is an opinionated system — full lifecycle from spec to PR.

- vs Devin: OmoiOS is open-source, self-hostable, shows you the plan before executing. Devin is a black box.

Built with Claude Agent SDK + FastAPI + PostgreSQL + Next.js 15. Apache 2.0 — fork it, self-host it, build on it.

Happy to go deep on the spec pipeline, the validation loop, or the multi-agent coordination.
by D-Machine | 2026-03-05 16:08:55+00:00
I'm not sure it is actually all that clear that pure nicotine products really are so addictive as people believe. E.g. most studies claiming such addictiveness may simply be because those that get addicted to patches / gum were already addicted to cigarettes (or other classic tobacco product) prior. See e.g. Gwern's notes on the topic.

https://gwern.net/nicotine#habit-formation

https://gwern.net/nicotine#dependence
by Tepix | 2026-03-05 16:08:55+00:00
These beams are much harder to detect and eavesdrop upon. You increase the difficulty for a remote attacker. I wouldn't stop encrypting the data, however:
The Alphasat TDP‑1 has a telescope with an 135mm aperture. The beam diameter is likely to be at least 700m wide according to the diffraction limit.
Show HN: LiberClaw, deploy AI agents that run 24/7 on their own VMs
by moshemalawach | 2026-03-05 16:09:03+00:00
LiberClaw is an open-source platform for deploying AI agents that run around the clock on dedicated virtual machines. You define what an agent does with markdown skills file, deploy it, and it keeps working whether you're at your desk or not. The agent system code is on GitHub: https://github.com/Libertai/liberclaw-agent

There are 61 agents running on the platform right now across 578 conversations, with 99.7% uptime. Each agent gets its own VM with its own filesystem, database, and HTTPS endpoint. Inference runs through open models (Qwen3 Coder, GLM-4.7) so there are no API keys to manage from OpenAI or Anthropic.

Agents have persistent memory across conversations, a heartbeat system for background tasks, and real tools: bash, file operations, web fetch, web search, and the ability to spawn subagents for parallel work. You can build code review bots, research agents, personal assistants, monitoring tools — anything that benefits from running continuously.

Free tier is 2 agents, no credit card. Deployment takes under 5 minutes.

- App: https://app.liberclaw.ai
- Source of the agents: https://github.com/Libertai/liberclaw-agent

If there are requests and an appetite for it, I can opensource the platform code too (it manages a pool of prepared VMs on aleph cloud and gives them to users as they request one).
by notepad0x90 | 2026-03-05 16:09:06+00:00
Block lists will always be used for one reason or another, in this case these are verified malicious sites, there is no subjective analysis element in the equation that could be misconstrued as censorship. But even if there was, censorship implies a right to speech, in this case Google has the right to restrict the speech of it's users if it so wishes, matter of fact, through extensions there are many that do censor their users using Chrome.
by mrprincerawat | 2026-03-05 16:09:10+00:00
You're right, effort ≠ value. I've caught myself spending days "perfecting" things that had zero impact on the user just because the grind felt productive. The post wasn't about AI being bad, I use it daily and wouldn't go back. Just a personal observation that the grind, even the unnecessary parts, is what taught me to build in the first place.
by epicprogrammer | 2026-03-05 16:09:21+00:00
Having spent some time in the anti-abuse and Trust & Safety space, I always take these vendor reports with a massive grain of salt. It’s a classic case of comparing apples to vendor-marketing oranges. A headline screaming about an 84% miss rate sounds like a systemic collapse until you look at the radically different constraint envelopes a global default like GSB and a specialized enterprise vendor operate under.

The biggest factor here is the false-positive cliff. Google Safe Browsing is the default safety net for billions of clients across Chrome, Safari, and Firefox. If GSB’s false-positive rate ticks up by even a fraction of a percent, they end up accidentally nuking legitimate small businesses, SaaS platforms, or municipal portals off the internet. Because of that massive blast radius, GSB fundamentally has to be deeply conservative. A boutique security vendor, on the other hand, can afford to be highly aggressive because an over-block in a corporate environment just results in a routine IT support ticket.

You also have to factor in the ephemeral nature of modern phishing infrastructure and basic selection bias. Threat actors heavily rely on automated DGAs and compromised hosts where the time-to-live for a payload is measured in hours, if not minutes. If a specialized vendor detects a zero-day phishing link at 10:00 AM, and GSB hasn't confidently propagated a global block to billions of edge clients by 10:15 AM, the vendor scores it as a "miss." Add in the fact that vendors naturally test against the specific subset of threats their proprietary engines are tuned to find, and that 84% number starts to make a lot more sense as a top-of-funnel marketing metric rather than a scientific baseline.

None of this is to say GSB is perfect right now. It has absolutely struggled to keep up with the recent explosion of automated, highly targeted spear-phishing and MFA-bypass proxy kits. But we should read this report for what it really is: a smart marketing push by a security vendor trying to sell a product, not a sign that the internet's baseline immune system is totally broken.
by piloto_ciego | 2026-03-05 16:09:32+00:00
This is actually my theory on why we're behaving so stupidly right now en masse.

I'm sure there's other papers out there, but this is the first one for this post: https://www.sciencedirect.com/science/article/pii/S036013232...

Anyway, CO2 levels rise on planet earth, which cause indoor levels to rise too. As it turns out, because of ventilation and such, indoor levels are always a bit higher than outdoor levels. We cross some critical threshold and it gets really hard for us to take on complex cognitive tasks and make good decisions. This effects everyone equally more or less a bit worse at planning, a bit worse at solving problems, a bit worse and making critical decisions.

In the long run, planners make worse decisions, governments make work decisions, voters make worse decisions, students perform more poorly... you get the picture. Over 20 or 30 years these bad decisions start to ramp up into meaningful impacts on the world. At risk of "post hoc ergo proctor hoc"-ing myself, the tipping point for this being somewhere close to 400ppm would make a lot of sense, because people seem to be noticeably dumber some time after 2014 ish? Hard to really pin it down though, but once CO2 levels started to routinely crest over that 1000ppm it seems to me that the world started to get a lot crazier.

Like, we can blame it on one politician we don't like or another, or on bad economic forecasting, or on the schools, or on latent racism / sexism / whatever-ism. To be clear, those are all legitimate concerns, but at the end of the day we're just animals more or less stuck on this orb zipping through the cosmos and if we're suddenly unable to do high level reasoning as well wouldn't you expect to see an increase in "dumb ideas" being accepted?
by bendmorris | 2026-03-05 16:09:37+00:00
You're going to get a lot of "skill issue" comments but your experience basically matches mine. I've only found LLMs to be useful for quick demos where I explicitly didn't care about the quality of implementation. For my core responsibility it has never met my quality bar and after getting it there has not saved me time. What I'm learning is different people and domains have very different standards for that.
by pjc50 | 2026-03-05 16:09:49+00:00
All these things can be true at the same time:

- fossil fuels have provided huge benefits

- the accumulation of CO2 in the atmosphere is causing gradually increasing problems that will eventually become severe in some places

- a lot of people made a lot of money along the way

- at some point, some people chose to lie about the problems

- lying about the problems is morally wrong

- the transition off fossil fuels will be expensive

- that is not a sufficient reason not to do it
by spwa4 | 2026-03-05 16:09:57+00:00
Why? Europeans never actually colonized anything but America. If you read your history you will see that it was the Roman Empire that started colonizing Africa, but 95% of the colonizing was done by various islamic empires, and Europe inherited those when muslims decided to end islam (the state, in the west known as "the Ottoman empire") ... and the Iranian mullahs see themselves as bringing those empires back.
by butterbomb | 2026-03-05 16:10:02+00:00
Funny. At least since Covid, I’ve noticed a number of employers, often at municipalities or other governments, but sometimes at private companies, are adding terms that employees cannot use any nicotine products whatsoever. What’s even stranger is the always go out of their way to explicitly note that non tobacco cessation aids are not allowed either. Seems like pure virtue signaling, though at least one person has suggested to me that the companies engaging in this are serious and go as far as blood testing.
by happyopossum | 2026-03-05 16:10:03+00:00
Every single proposal for a national sales tax, consumption tax, or 'flat' tax put forward by the right has been shown over and over again to not be regressive - usually through the implementation of prebates (literally a check written to lower income people every year/quarter to cover a portion of the taxes they will pay).

Whether or not these schemes would work is debatable, but to claim that they show an MO of regressive taxes is just false.
Show HN: Attn – Markdown viewer and editor in a <20MB binary (Rust)
by lightsofapollo | 2026-03-05 16:10:11+00:00
I use Claude Code as my primary dev environment. It generates a lot of markdown. Planning docs, architecture notes, task lists. I wanted something purpose-built for reading markdown. Not a browser tab, not a preview pane in an editor. A real app I can launch from the terminal.

VS Code's markdown preview is fine but I don't really use VS Code. I wanted something Claude Code could launch for me and get a nice readable window.

So I built attn. One command, OS webview window, under 20MB. No Electron, no bundled Chromium.

Some things that ended up being useful:

npx attnmd README.md and it just works. Rust binary distributed through npm so you don't need cargo or a homebrew tap.

Live reload. I'm reading a plan while the agent is still writing it. Save the file, see it update.

Full ProseMirror editor with syntax highlighting, math, and mermaid. I annotate plans inline without opening another tool.

Mermaid diagrams render inline. Agents love generating mermaid.

Stack: Rust (wry/tao wrapping the OS webview — WebKit on macOS, WebKitGTK on Linux), Svelte 5 + ProseMirror frontend compiled by Vite and embedded into the binary at build time.

npx attnmd README.md to try it, cargo install attn to build from source. MIT licensed, source at github.com/lightsofapollo/attn.
by OutOfHere | 2026-03-05 16:10:15+00:00
I strongly urge against consuming any tobacco or nicotine product. At the very least, it's very bad for your heart in pretty much every form, whether pure or impure, smoked or absorbed. Besides being directly bad for the heart, nicotine also metabolizes to carcinogens.

If you need a boost beyond caffeine, consider a square of 95% or 100% dark chocolate. It works. It too stresses the heart mildly, and can aggravate reflux a lot, but overall it's significantly safer than any tobacco product. You can also eat more of it if as needed.

The only sane time to take pure nicotine might be if someone is dying from Covid, their lungs are collapsing, and one desperately needs a daytime breathing boost.
by api | 2026-03-05 16:10:16+00:00
I've been wondering how long it would take for tobacco to make a comeback given that we seem to be in a weird era where it's some kind of flex to embrace idiotic ideas.

Nicotine (without tobacco e.g. Zyn or gum) does seem to have some nootropic-ish properties but it's vastly inferior to a lot of other things and has major addiction/tolerance problems. It's not a great performance enhancer for anything but very sporadic use.
by intrasight | 2026-03-05 16:10:36+00:00
That article doesn't even mention nonresident importers (NRIs). The percentage that are NRIs is not public information but it is believed to have grown during this trade conflict.

What got my attention on this was this HN comment by rstuart4133:

"There are Non-Resident Importers, which are foreign companies that import goods into the USA, but do not have a presence in the United States. About 15% of USA imports come through NRIs. For them this reversal sets up a true irony. Trump effectively forced US citizens to pay more the imported goods. He thought that money would go to the USA treasury. Now the US treasury has to pay it back, so it is a free gift to the exporting countries. Like China. Truly delicious."
by Shank | 2026-03-05 16:10:37+00:00
I would actually argue that Classic WoW and OSRS are not good examples. These games already existed. For OSRS, the mass cancellation of subscriptions immediately following game updates was a clear wallet vote. Most feature requests aren't asking for the return of something people already liked.

Classic WoW is also not as successful as OSRS, which is why they're exploring Classic+. Even OSRS, which was born on nostalgia, also gets significant new content updates (albeit polled).
by ConvertlyAI | 2026-03-05 16:10:39+00:00
I love this approach to verification. I literally just launched my own AI formatting engine yesterday, and the hardest part wasn't the generation—it was building strict system-level guardrails to stop the model from outputting generic fluff words and breaking my slide formatting. Are you doing this pre-execution verification purely through secondary prompt checks, or are you running it through a separate smaller model first?
by rush340 | 2026-03-05 16:11:05+00:00
Em dashes in every other sentence. I've never seen an actual person do that. The language in general reads exactly it's written by an LLM:

"The blah blah didn't just start as blah. It started as blah..."
"First came blah -- blah blah blah"
"And now: blah"

It's a distinctly AI writing style. I do wonder if we'll get to a point where people start writing this way just because it's what they're used to reading. Or maybe LLMs will get better at not writing like this before that happens.
by jdup7 | 2026-03-05 16:11:12+00:00
Fair point in isolation that number doesn't look good. The important context is that this dataset was built to test phishing detection, not to measure false positive rates on normal traffic. It's sourced from our threat intelligence tooling so it's almost entirely malicious URLs by design. The 9 clean sites aren't a random sample of everyday browsing. They're sites that were submitted as suspicious and turned out to be legitimate so they're basically the hardest possible set of clean pages to correctly classify. This seems like a common critique and we definitely could have done a better job of explaining the methodology. Going forward we will include numbers from daily use to give a better picture of FP rate.
by Dunsinagb | 2026-03-05 16:11:20+00:00
Interruptly is a behavioral pattern-awareness app designed to help users understand the triggers behind their habits and impulses. The app focuses on helping people recognize patterns in behavior by logging context, emotions, and triggers associated with habits.

Key features include:
• Habit interruption tracking
• Behavioral pattern insights
• Context-aware logging
• Analytics-driven habit awareness

Built with SwiftUI and AI-assisted development tools, exploring how data and behavioral insights can help people make better decisions.
by thewebguyd | 2026-03-05 16:11:45+00:00
To be fair on the Blizzard example, I think Blizzard could have also made the player base just as happy by, doing as your quote said, understanding the underlying problem.

It wasn't only a "we want WoW classic bug for bug," it was "the modern game has become so unrecognizable that it's basically WoW 2.0, you ruined it with the modern systems"

Blizzard could have rolled back LFR/LFG, class homogenization, brought back complicated and unique talent trees, remove heirlooms, re-add group guests and world mini-bosses, remove flying, etc. and players likely would have been happy.

Classic will only save them for so long without them making new content, but using classic's systems. So in a way, I think the point still stands, you have to understand what the underlying problem is. Users do generally know what they want, but they don't always know how to ask for it.
by epicprogrammer | 2026-03-05 16:11:51+00:00
It’s an interesting throwback to SEDA, but physically passing file descriptors between different cores as a connection changes state is usually a performance killer on modern hardware. While it sounds elegant on a whiteboard to have a dedicated 'accept' core and a 'read' core, you end up trading a slightly simpler state machine for massive L1/L2 cache thrashing. Every time you hand off that connection, you immediately invalidate the buffers and TCP state you just built up. There’s a reason the industry largely settled on shared-nothing architectures like NGINX having a single pinned thread handle the entire lifecycle of a request keeps all that data strictly local to the CPU cache. When you're trying to scale, respecting data locality almost always beats pipeline cleanliness.