Microsoft for DevelopersWaldek Mastykarz5 min readintermediate
Your AI coding agent evaluation is only as good as its sandbox
Summary
Evaluating AI coding agents requires a robust sandbox to prevent agents from retrieving answers from the environment, which can invalidate tests of internal knowledge. A correct answer doesn't guarantee a valid measurement if the agent accessed information it shouldn't have, highlighting the need to define sandboxes by information boundaries rather than just tool restrictions. Always review agent…
- A correct agent answer can invalidate an evaluation if the agent retrieved information from the environment rather than using internal knowledge.
- Sandboxes should enforce information boundaries across all agent capabilities, not just restrict individual tools, as agents will find alternative routes.
- Agents can access information from the filesystem, installed software, and environment details, even when web access is blocked.
- Always inspect the full agent trajectory, including tool calls and observations, to verify how an answer was reached.
Engineers evaluating AI coding agents need to understand how to design effective sandboxes to ensure their evaluations accurately measure agent capabilities and prevent misleading results.
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