Agentic AI leverages LLMs by integrating specialized agents and tools, enabling collaborative task execution beyond content generation. This architecture empowers autonomous workflows, addressing complex problems from automated planning to diagnostic support. By orchestrating diverse agents, AI actively strategizes and executes solutions.

We will explore agentic system implementation using LangGraph and Semantic Kernel, focusing on agent definition, types, and external system integration. Attendees will learn to construct robust agent flows, enabling AI applications to transcend passive interaction and engage in real-world task execution.

This session equips participants to implement agentic strategies in existing and future applications. Understanding agent orchestration and tool integration empowers the design of AI systems capable of active problem-solving, fostering innovation and efficiency.