When do AI agents need permission boundaries?
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Permission boundaries for AI agents, practical and timely for agent safety.
AI agents become execution surfaces once they call tools, making tool access equivalent to production access. Rather than relying on prompt engineering or natural-language tool descriptions, a secure architecture uses a deterministic policy layer that decouples tool selection from authorization, with a fail-fast order that checks static risk, authorization, and strict argument schemas before execution. A reference implementation on GitHub demonstrates this pattern by blocking unsafe paths and enforcing role-based scopes (viewer, operator, admin) where unknown roles fail closed.