Sandboxed.Sh

sandboxed.sh tackles a specific pain: AI coding sessions that time out after 30 minutes. For anyone doing multi-hour refactors or migrations, that's a dealbreaker. This tool lets you fire off a task and walk away. The container isolation is the standout feature. Each project gets its own Docker environment with its own runtime, dependencies, and secrets. You can run Claude Code on your Node project and Codex on your Python project simultaneously without cross-contamination. The skills library stored in git is clever but incomplete. You define agent behaviors as version-controlled commands and rules. In practice, writing good skills takes iteration. Expect to spend time crafting prompts that encode your team's patterns. Setup is about 5 minutes if you're comfortable with Docker, nginx, and a domain. The docs are clean and Claude/Cursor can auto-deploy. But you still need a server (≈$30/mo) and basic ops skills. Non-technical users should look elsewhere. Where it bites: the dashboard is a Next.js app you deploy yourself (Vercel is free, but still extra steps). No managed cloud version exists. If your server goes down, agents stop. There's no built-in load balancing or high availability. Compared to just running Claude Code locally with nohup, sandboxed.sh gives you a proper dashboard, mobile monitoring, and structured skill management. Compared to Cursor's agent mode, it trades convenience for control and persistence. We'd reach for this when code sovereignty is non-negotiable and tasks run longer than an hour. For quick debugging or one-shot codegen, simpler tools win. On balance, sandboxed.sh fills a genuine gap—just be ready to babysit a server.