Securing Agentic AI Fundamentals – No BS Guide – Part 1 (www.subhashdasyam.com)

A new guide on Agentic AI fundamentals emphasizes the significant shift in operational risk when moving from traditional large language model (LLM) applications to agentic systems capable of taking autonomous actions. Unlike conventional LLM apps that merely generate text, agentic systems can interact with APIs, execute workflows, and communicate with other agents, which raises various security concerns. The guide offers a framework for organizations to assess agent capabilities and associated risks, highlighting the importance of understanding the agent's operational permissions, potential vulnerabilities, and necessary safeguards. The guide introduces key concepts like the "agent loop," which includes perception, reasoning, action, and observation, and underscores the varying levels of autonomy that can be applied to agents, ranging from mere advisors to fully autonomous systems with significant control over operations. It warns that while organizations may aspire to deploy self-sufficient agents, many lack the foundational security measures and culture needed to manage the higher risks effectively. Emphasizing the importance of robust policies, monitoring, and continual updates to prompt and security mechanisms, the guide serves as a crucial resource for navigating the complexities of deploying agentic AI safely.