As AI agents gain access to enterprise systems, APIs, and sensitive data, balancing autonomy with control becomes a critical engineering challenge. Giving agents the permissions needed to execute complex tasks also introduces risks around unauthorized actions, data exposure, and unintended consequences. Rather than relying on prompts or standalone safety checks, engineers must embed guardrails directly into system architecture. This panel explores how teams can design secure agent permissions, enforce operational boundaries, and maintain oversight without limiting agent capabilities. Key takeaways: → Designing least-privilege access and permission controls across agent tools, APIs, and enterprise systems. → Implementing architectural guardrails to prevent unauthorized actions and unintended consequences. → Balancing agent autonomy with human approval, policy enforcement, and real-time intervention.