When you're running AI coding agents in production — Claude Code writing database migrations, Codex refactoring across repositories, OpenCode churning through test suites — you need somewhere safe to execute the code they generate. Three patterns have emerged as the field consolidates: Daytona , purpose-built sandbox infrastructure that just raised a $24M Series A ; AgentBox , a lightweight Docker-based SDK that recently landed on Hacker News ; and DIY harnesses , the roll-your-own approach with containers, tmux, and custom permission scripts. This post compares all three on the dimensions that actually matter for agent workloads — isolation model, setup cost, SDK breadth, agent compatibility, and production readiness — so you can choose with confidence rather than guess. TL;DR Daytona : Production-ready, sub-90ms sandbox creation, SDKs in Python/TypeScript/Ruby/Go, documented agent integrations. Best for teams running agents at scale. AgentBox : Simple Docker-based isolation, minimal overhead, new entrant.…