Agent Sandbox is only a technical label.
The term changes buyer and operator decisions when tool access, data exposure, or support ownership is involved.
AI
Agent Sandbox
An agent sandbox is a constrained environment where AI tool use can be tested without exposing production systems to uncontrolled actions.
Definition
An agent sandbox is a constrained environment where AI tool use can be tested without exposing production systems to uncontrolled actions. In PRO71 delivery, the term matters because it changes how AI tool access is scoped, reviewed, observed, and supported.
In practical context
Agent Sandbox is used when teams need clearer boundaries around MCP, agent workflows, production diagnostics, or security gates.
Why it matters
Agent Sandbox becomes more useful when it is tied to one permission, evidence, or operating decision.
Common misconceptions
Agent Sandbox can be decided after launch.
For enterprise AI systems, this boundary should be designed before production exposure.
FAQ
Questions teams ask before they start
What does Agent Sandbox mean in practice?
It describes a concrete boundary or pattern that affects how teams govern and operate AI-enabled systems.
Why does PRO71 define Agent Sandbox?
We define it so business, security, and delivery teams can make the same decision with shared language.