Evidence-first authority page
Docker Sandboxed Execution AI Agents
Why running an AI coding agent's code execution inside Docker matters, and how to configure it correctly.
Direct answer
A coding agent that executes generated code should do so inside a Docker container with no access to the host filesystem or network beyond what's explicitly required — this contains the risk of a wrong or unintended command to the container, rather than the developer's actual machine.
Last reviewed 2026-08-29
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Why this matters for coding agents specifically
A coding agent that runs the code it generates is executing unreviewed code by definition — that's the whole point of an autonomous test-and-iterate loop. Sandboxing that execution in a container is the practical mitigation, containing a mistaken `rm -rf`, an infinite loop, or an unintended network call to the container rather than the host.
Configuration essentials
- Mount only the project directory being worked on, not the host filesystem broadly.
- Set memory, CPU, and execution-time limits.
- Use a fresh container per task rather than a long-lived one that accumulates state across unrelated work.