In this session, we'll compare RAG (Retrieval-Augmented Generation) and CAG (Contextual-Augmented Generation), exploring their distinct approaches to enhancing generative AI. We'll dive into optimizing RAG using AI agents and vector databases, demonstrating how these tools can efficiently handle large-scale data and solve complex problems. Finally, we’ll showcase how AI agents can autonomously tackle intricate challenges, advancing the capabilities of AI systems.