What is AI agent sandboxing and how does it work?

AI agent sandboxing isolates agent execution in a controlled environment where actions can be evaluated, tested, and validated before affecting production systems — but most "sandboxes" only isolate the compute environment, not the agent's tool calls and API access.

Levels of AI agent sandboxing:

• Compute sandbox (containers, VMs): Isolates the runtime but the agent can still make API calls, send emails, and access databases from within the container
• Network sandbox (VPC, firewall rules): Restricts outbound connectivity but can't understand the semantic meaning of allowed traffic
• Execution sandbox (Exogram's approach): Evaluates every proposed action against deterministic policy rules regardless of the runtime environment — works across containers, serverless, and bare metal

The Exogram Proving Ground demonstrates execution-level sandboxing. The agent sends exactly the same API call it would send in production. The same 8 policy gates evaluate it. But the sandbox skips database writes and audit persistence. The result: you test real governance behavior without production risk. When you move to production, the governance layer is identical — you've already proven it works.