An AI agent published a hit piece on me
Previously: AI agent opens a PR write a blogpost to shames the maintainer who closes it - https://news.ycombinator.com/item?id=46987559 - Feb 2026 (582 comments)
Gemini 3 Deep Think
https://twitter.com/GoogleDeepMind/status/202198151040070909...
GPT‑5.3‑Codex‑Spark
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Major European payment processor can't send email to Google Workspace users
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Launch HN: Omnara (YC S25) – Run Claude Code and Codex from anywhere
Hey y’all, Kartik, Ishaan, and Christian from Omnara (https://www.omnara.com/) here. We’re building a web and mobile agentic IDE for Claude Code and Codex that lets you run and interact with coding agents from anywhere. Omnara lets you run Claude Code and Codex sessions on your own machine, and exposes those sessions through a web and mobile interface so you can stay involved even when you’re away from your desk. Think of it like Claude Code Desktop or Conductor, except you can continue your sessions on your phone.
Here’s a demo of the web and mobile apps - https://youtu.be/R8Wmy4FLbhQ
We started using Claude Code early last year and quickly ran into a pattern: agents could work for long stretches on their own, but progress would stall whenever they needed follow-up input. If that happened while we were away from our desks, everything just paused. We looked at remote agent solutions like Codex Web and Devin, which were the main options at the time, but they ran in remote VMs, and we wanted our coding agent to run in our own environment. Our first attempt at solving this was a lightweight wrapper that streamed messages from the Claude Code CLI to a mobile app, but that approach ended up being fragile and hard to maintain.
As the Claude Agent SDK matured, it gave us enough control to rewrite Omnara from scratch and run the agent loop directly. We chose to build a GUI across web and mobile instead of a TUI or CLI, because we think GUIs are generally more ergonomic for working with agents and code, especially on mobile. We still preserve the main strength of CLIs and TUIs: running anywhere, including on headless machines.
Omnara keeps that property by running a small headless daemon on the user’s machine (or a remote VM) that hosts the agent loop. The daemon maintains an authenticated, outbound WebSocket connection to our server, which relays messages between the agent running on the user’s machine and any connected web or mobile clients. Because the daemon only makes outbound connections, there’s no need for exposed ports, SSH access, or tunneling on the user’s machine.
In our first version of Omnara, users liked that agent sessions ran in their own environment, but they still depended on the machine staying online. Some users ran Omnara on a remote machine that stayed up, which worked well for them, though most still did most of their work on laptops. In the current version, Omnara can continue an agent session in a hosted remote sandbox when your local machine goes offline.
The conversation state of an agent is already persisted on our server, and you can optionally enable cloud syncing for the working code. When syncing is enabled, Omnara creates git commits at each turn in the conversation and pushes them to our server, so execution can resume from the same state regardless of whether it continues locally or in the cloud. If you continue working in a remote sandbox, you can later pull any changes back into your local environment when you return to your machine. Environment parity in the sandbox isn’t perfect yet, but in practice, missing dependencies are usually easy to resolve by asking the agent to install them.
Another thing we learned from using the initial version of Omnara is that mobile is fine for quick interactions, but not great for extended back-and-forth. Users asked for a hands-free way to keep agents moving while walking, driving, or doing something else, which led us to add a voice agent. Coming from more traditional software engineering backgrounds, we honestly thought coding by talking to a voice agent would be gimmicky and added it mostly as a fallback.
What surprised us is how useful the voice agent ended up being in practice. When working with coding agents, being redundant and overly explicit usually helps, and people naturally give more detail when speaking than when typing. Going back and forth with the agent as the conversation unfolds tends to produce a much more solid plan than trying to one-shot it with a prompt (this could technically also be done over text, but talking and iterating over voice feels easier and more natural). It’s also just fun. Talking through an idea with an agent while out on a walk is a lot more enjoyable than staring at a terminal screen.
To try it out, open your terminal and download Omnara with
curl -fsSL https://omnara.com/install/install.sh | bash
then run omnara inside any git repository. This starts a headless Claude Code or Codex session in that repo, which immediately appears in the Omnara web and mobile apps. From there, you can continue that session or start new ones remotely (with or without worktrees) and switch between the web and mobile clients without interrupting the agent.Omnara is free for 10 agent sessions per month, then $20/month for unlimited sessions. When agents run in your own environment, you can use your existing Claude or Codex subscription, so there’s no need to pay us for additional tokens. If you use Claude Code or Codex, we’d love to hear your feedback on Omnara!
Shut Up: Comment Blocker
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Improving 15 LLMs at Coding in One Afternoon. Only the Harness Changed
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Culture Is the Mass-Synchronization of Framings
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Apache Arrow is 10 years old
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Warcraft III Peon Voice Notifications for Claude Code
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US businesses and consumers pay 90% of tariff costs, New York Fed says
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The Future for Tyr, a Rust GPU Driver for Arm Mali Hardware
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The "Crown of Nobles" Noble Gas Tube Display (2024)
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1D Cellular Automata Playground
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ai;dr
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I Wrote a Scheme in 2025
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Run Pebble OS in Browser via WASM
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So many trees planted in Taklamakan Desert that it's turned into a carbon sink
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Show HN: 20+ Claude Code agents coordinating on real work (open source)
Single-agent LLMs suck at long-running complex tasks.
We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress.
How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents
We tested this on a Putnam-level math problem, but the pattern generalizes to things like refactors, app builds, and long research. It’s packaged as a Claude Code skill and designed to be small, readable, and modifiable.
Use it, break it, tell me about what workloads we should try and run next!
Apple patches decade-old iOS zero-day, possibly exploited by commercial spyware
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