Firecracker

Ever tried running hundreds of sandboxed Linux environments for agentic RL training? Docker is too heavy for rapid fork-and-destroy, and spinning up real VMs takes ages. Then I spotted AgentENV on GitHub Trends — 1,589 stars in 6 days, built by the kvcache-ai team to power Kimi K3’s agentic RL training. It is a Rust-based runtime that wraps Firecracker microVMs with snapshot-resume fast enough to boot a sandbox in under 50ms. Here is what I found after taking it for a spin. ...

Ever handed your AI agent a task and crossed your fingers it wouldn’t trash your local environment? Yeah, me too. That sinking feeling when Claude starts writing install scripts on your actual machine. Or worse — when it does something unexpected and now you’re digging through bash history trying to undo it. So I’ve been down the E2B route — wrote about it here, and it’s a solid sandbox. But sandboxes are for running code. What if your agent needs a whole machine? Plus a desktop with a browser, a terminal, root access, the works? ...