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Show HN: Ovumcy – self-hosted menstrual cycle tracker

https://github.com/terraincognita07/ovumcy
1•terrain07•17s ago•0 comments

Show HN: Sheila, an AI agent that replaced our accounting flow

https://soapbox.pub/blog/announcing-sheila/
3•knewter•8m ago•1 comments

Qualcomm CEO: 'Resistance Is Futile' as 6G Mobile Revolution Approaches

https://fortune.com/2026/03/03/qualcomm-ceo-resistance-is-futile-6g-mobile-revolution-approaches/
2•m463•9m ago•1 comments

Show HN: NeoNetrek – modernizing the internet's first team game (1988)

https://neonetrek.com
1•yuriksan•11m ago•0 comments

Show HN: Natural language queries for Prometheus Kafka metrics (StreamLens)

https://github.com/muralibasani/streamlens
1•muralibasani•11m ago•0 comments

Satellite firm pauses imagery after revealing Iran's attacks on US bases

https://arstechnica.com/space/2026/03/satellite-firm-pauses-imagery-after-revealing-irans-attacks...
1•consumer451•13m ago•0 comments

China Suspected in Breach of FBI Surveillance Network

https://www.wsj.com/politics/national-security/china-suspected-in-breach-of-fbi-surveillance-netw...
2•JumpCrisscross•13m ago•0 comments

Show HN: I created list of directories (1000) to create free backlinks

https://kitful.ai/directories
1•eashish93•16m ago•0 comments

Fishing crews in the Atlantic keep accidentally dredging up chemical weapons

https://arstechnica.com/health/2026/03/fishing-crews-in-the-atlantic-keep-accidentally-dredging-u...
2•jnord•17m ago•0 comments

The National Videogame Museum Has Acquired the Mythical Nintendo PlayStation

https://www.engadget.com/gaming/the-national-videogame-museum-has-acquired-the-mythical-nintendo-...
2•breve•20m ago•0 comments

C# Strings Silently Kill Your SQL Server Indexes in Dapper

https://consultwithgriff.com/dapper-nvarchar-implicit-conversion-performance-trap
5•PretzelFisch•21m ago•0 comments

Show HN: I open-sourced my Steam game, 100% written in Lua, engine is also open

https://github.com/willtobyte/reprobate
1•delduca•22m ago•0 comments

The White House: Touchdown

https://twitter.com/WhiteHouse/status/2030051395294941427
2•TheAlchemist•22m ago•3 comments

Capability-Tiered AI Governance Architecture (CEGP)

https://github.com/babyblueviper1/ai-governance-architecture
2•babyblueviper1•24m ago•1 comments

A new chapter for the Nix language, courtesy of WebAssembly

https://determinate.systems/blog/builtins-wasm/
2•birdculture•25m ago•0 comments

Shipping a Button in 2026 [video]

https://www.youtube.com/watch?v=xE9W9Ghe4Jk
1•Dhvani35729•26m ago•0 comments

Show HN: Stream-native AI that never sleeps, an alternative to OpenClaw

https://github.com/timeplus-io/PulseBot
1•gangtao•32m ago•0 comments

Show HN: Flompt – Visual prompt builder that decomposes prompts into blocks

https://github.com/Nyrok/flompt
1•hkonte•32m ago•0 comments

FBI investigating 'suspicious' cyber activity on system holding wiretaps

https://abcnews.com/Technology/wireStory/fbi-investigating-suspicious-cyber-activity-system-holdi...
1•campuscodi•33m ago•0 comments

Show HN: key-carousel - Key rotation for LLM agents

https://github.com/HalfEmptyDrum/Key-Carousel
4•EmptyDrum•33m ago•1 comments

Device that can extract 1k liters of clean water a day from desert air

https://www.tomshardware.com/tech-industry/device-that-can-extract-1-000-liters-of-clean-water-a-...
3•PaulHoule•36m ago•0 comments

Show HN: Sqry – semantic code search using AST and call graphs

https://sqry.dev
2•verivusai•36m ago•0 comments

The Window Chrome of Our Discontent

https://pxlnv.com/blog/window-chrome-of-our-discontent/
2•zdw•38m ago•0 comments

When Batteries Heat Up, This Membrane "Sweats" It Out

https://axial.acs.org/nanoscience/when-batteries-heat-up-this-membrane-sweats-it-out
1•geox•38m ago•0 comments

Show HN: Stratum - a pure JVM columnar SQL engine using the Java Vector API

https://datahike.io/stratum/
1•whilo•39m ago•1 comments

Wild crows in Sweden help clean up cigarette butts

https://www.samodobrevijesti.com/en/news/wild-crows-in-sweden-help-clean-up-cigarette-butts/
10•jhncls•39m ago•4 comments

Show HN: BLOBs in MariaDB's Memory Engine – No More Disk Spills for Temp Tables

https://jira.mariadb.org/browse/MDEV-38975
1•arcivanov•42m ago•1 comments

Tip me, my life depends on it (2021)

https://idiallo.com/blog/tip-me
2•foxfired•43m ago•0 comments

Show HN: OculOS – Give AI agents control of your desktop via MCP

https://github.com/huseyinstif/oculos
1•stif1337•44m ago•0 comments

New Strides Made on Deceptively Simple 'Lonely Runner' Problem

https://www.quantamagazine.org/new-strides-made-on-deceptively-simple-lonely-runner-problem-20260...
1•ibobev•48m ago•0 comments
Open in hackernews

Show HN: ClaudeOS – What if Claude Code managed your operating system?

https://github.com/jacopone/nixos-config
2•jak0•8h ago

Comments

jak0•8h ago
NixOS + Flakes turns your entire operating system into a folder of .nix files. That folder is a git repo. Give Claude Code access to that repo and it can manage everything — packages, services, hardware config, shell, bootloader. I've been calling this ClaudeOS: an operating system entirely managed by Claude Code.

I'm not a developer. My background is data science and finance. Six months ago I couldn't tell you what a Nix derivation was.

I started because I wanted Claude Code to manage my system, not just my code. Tried it on Ubuntu first and it was a disaster — Claude would edit .bashrc and break my shell, install packages that conflicted with each other, no way to undo any of it cleanly. A friend mentioned NixOS, I installed it on my Framework laptop, and within a week I realized this is what AI-assisted system management should look like. Claude edits a .nix file, I rebuild, if it breaks I roll back in one command. No more "what did the AI just do to my system?"

It snowballed from there. ~470 commits later I'm running 7 machines off this config — my Framework 16 dev workstation, a ThinkPad, and a bunch of business laptops for people who've never opened a terminal. Two profiles: a "tech" profile with 350+ packages and a full AI toolchain (Claude Code, Cursor, local speech-to-text), and a "business" profile with ~40 curated packages for office use. Adding a new machine is three lines in flake.nix.

Some things I built along the way:

A script that spins up Claude Code in a sandboxed git worktree with bubblewrap + seccomp so it can work autonomously in the background. It runs in a tmux session and loops with fresh context up to 5 times. I use it for overnight refactoring.

Custom NixOS installer ISOs — I ship a USB stick to someone, they plug it in, and they get a working system with Claude Code pre-configured as their "sysadmin." They ask Claude to install software, Claude edits the config, they rebuild. I manage their machines remotely via git push.

CI/CD with BATS tests, ShellCheck, security scanning. A two-branch model where personal (my dev branch) auto-syncs to master via CI with path sanitization so nothing personal leaks to the public repo.

The core insight: NixOS is the only OS I've used where AI can't permanently break anything. Declarative config means Claude always knows the exact system state. Atomic upgrades mean every rebuild either succeeds completely or doesn't happen. If something goes wrong, I pick the previous generation from the boot menu. I've bricked my system maybe 15 times and recovered in under a minute every time.

What still sucks: the Nix learning curve is real even with AI. Claude writes non-idiomatic Nix all the time and I can't always tell. Flake lock updates break things in ways that take hours to debug. Error messages are famously terrible. And NixOS is not for everyone — it's a tradeoff between upfront complexity and long-term reliability.

Is anyone else doing something like this? Not just using AI to write code, but to manage and evolve their actual operating system?

Repo: https://github.com/jacopone/nixos-config

battery_staple_•7h ago
> I started because I wanted Claude Code to manage my system, not just my code.

I have two reactions to this.

First: respectfully, this is hilarious. LLMs are good at many things, but judgement is not one of them. At the outset, this was firmly in the "terrible ideas" category. (EDIT: ugh; I misread you. I thought you said Claude Code wanted to manage your system. I need more coffee...)

Second: sometimes from terrible ideas come great creativity. (I'm actually not sure what epistemic basis creativity flows from, if not simply the habit of adding entropy to a search path, and you sure chose a high entropy path!) I don't know anything about the stack you chose, but I've spent many hours almost being enticed by https://guix.gnu.org/ and this sounds similar. And the part where you have recovered from a borked system about 15 times is genuine evidence that you're doing something right. I applaud your grit and hope you're having as much fun as it sounds like you are.

jak0•7h ago
Ahahaha yes I totally agree - but my point is that nixos seems to be the right candidate to at least try to manage the entropy :) Or maybe it just gives you this impression.

I will definitely look into guix thanks!

Zeetah•7h ago
Great experiment!

Let's say you have 15 programs installed. You use programs 1-5 multiple times a day, 6-10 every few days, 11-15 every couple of weeks.

The AI makes a change. It rebuild the image. Things are working.

A few days later, you go to use one the 10-15 programs that haven't been used for a week or two and it doesn't work. The change could have been that day or a couple of weeks ago. How do you remedy that? Thanks in advance for your insights.

jak0•7h ago
That's a real scenario and it's happened to me. The key is that NixOS keeps every previous generation — so when I discover program #12 is broken, I can nix store diff-closures to see exactly what changed between generations, or just boot into the last known-good generation from GRUB. In practice I do two things: I keep a quick smoke-test habit after rebuilds (open a couple of the less-used apps), and the git history tells me exactly which .nix change touched what. Since every rebuild is a commit, git bisect works on your OS the same way it works on code. It's not perfect — I've definitely had the "wait, when did this break?" moment. But the recovery path is always under a minute, which makes the cost of experimentation very low.