Agentic AI Architecture Explained | RAG vs Agents, Memory, Embeddings & Multi-Agent Systems

Description

In this video, we complete Phase 2 of the Build Agentic AI Systems series by breaking down the architecture behind modern Agentic AI systems. We explore: High-Level Architecture of an Agentic AI System The Agent Loop (Think → Plan → Act → Observe → Reflect) Memory in Agentic AI (Short-Term vs Long-Term) Embeddings Explained Vector Databases & Semantic Search RAG vs Agentic Systems Single-Agent vs Multi-Agent Architectures This video connects foundational AI concepts with real system design thinking — moving beyond chatbots into autonomous, goal-driven AI systems. If you're learning how to design scalable, production-ready Agentic AI systems, this Phase 2 breakdown gives you the architectural clarity you need before moving into execution and orchestration. Next: Execution & Orchestration Planning, tool calling, guardrails, observability, and more. 00:00 Introduction 00:24 High-Level Architecture of an Agentic AI System 02:56 The Agent Loop Explained 05:46 Memory in Agentic AI 08:00 Embeddings Explained 10:52 Vector Databases Explained 13:34 RAG vs Agentic Systems 14:36 Single-Agent vs Multi-Agent Architecture 15:28 Phase 2 Wrap-Up & Phase 3 Preview