SHURU
Local-First Sandboxes for AI Agents on macOS.
What it does
Lightweight Linux VMs powered by Apple Virtualization.framework. Ephemeral by default. No Docker required.
Does a similar job
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- MOMarinaBox: Open-Source Sandbox Infra for AI Agents2024 · github.com · ▲6
Hey everyone, We're excited to introduce MarinaBox, an open-source toolkit for creating isolated desktop/browser sandboxes tailored for AI agents. Over the past few months, we've worked on various projects involving: 1. AI agents interacting with computers (think Claude computer-use scenarios). 2. Browser automation for AI agents using tools like Playwright and Selenium. 3. Applications that need a live-session view to monitor AI agents' actions, with the ability for human-in-the-loop intervention. What we learned: All these scenarios share a common need for robust infrastructure. So,…
- PSPacific Slate: a self-hosted, model-agnostic multi-agent AI assistant28d ago · pacslate.com · ▲5
I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.
- RARun AI coding agents in real, local sandboxes, not Git worktreesApr 2026 · superhq.ai · ▲6
Hey HN, I built SuperHQ, an app that lets you run coding agents in local sandboxes (powered by Shuru). No custom UI wrapping the agents, they run as CLI/TUI like they were designed to. It just provides you the tools most of us (okay, maybe just me?) needed for running multiple coding agents in parallel without worrying about breaking your system or work environment. Each agent runs in its own microVM. You mount your projects in, writes go to a tmpfs overlay so your host is never touched, and you get a unified diff view to accept or discard changes. API keys never enter the sandbox, they…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
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AI · 19d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
