Agentic RAG Explained: AI That Can Plan, Use Tools, and Verify Answers

Description

Large Language Models are powerful, but they often hallucinate and struggle with complex reasoning. In this video, we explore **Agentic RAG**, a modern AI architecture that combines Retrieval-Augmented Generation with autonomous AI agents. Instead of simply retrieving documents and generating answers, Agentic RAG systems can plan tasks, use tools, retrieve information, and verify their own outputs. In this video you'll learn: • How traditional RAG systems work • Why normal RAG pipelines fail on complex problems • What makes Agentic RAG different • The architecture of an Agentic RAG system • How AI agents plan, retrieve, reason, and verify answers We walk through the core components including the data pipeline, planner agent, orchestrator agent, tool suite, and verification loop. If you're interested in **AI engineering, LLM systems, AI agents, or building advanced RAG architectures**, this video explains the key concepts behind modern AI research assistants. Topics covered: Retrieval-Augmented Generation (RAG) AI agents and autonomous reasoning Vector databases and embeddings LLM system architecture Verification loops to reduce hallucinations Subscribe to follow more videos about building real AI systems. #AI #RAG #AIAgents #MachineLearning #AIEngineering