Traditional software executes predefined logic in response to requests. Agentic systems observe their environment, make decisions, and act over time. This session introduces the core distinction that defines agentic AI and explains why existing mental models for building and operating software no longer fully apply. We’ll examine how state, memory, and decision authority change system behavior, introduce new failure modes, and complicate responsibility in production environments. The focus is on understanding what engineers must reason about differently once systems are allowed to act autonomously. This session sets the foundation for discussions on coordination, evaluation, and control throughout the Agentic AI track.