Agentic AI systems perform actions beyond just returning text, introducing operational risks. Key concepts include levels of autonomy, risks associated with agent actions, and the importance of monitoring and governance. Agents operate on a loop of perceiving, reasoning, acting, and observing, making security critical at each step. There are various trust boundaries when interacting with tools and data. To mitigate risks, architectures should implement a “Guarded Agent Loop” with layers for input processing, policy awareness, tool proxies, and output validation. Real-world examples illustrate the need for strict controls to prevent unauthorized actions and ensure compliance.
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