Agentic RAG: Advancing AI Information Retrieval (2025)

Description

Retrieval Augmented Generation (RAG) and Agentic RAG, a more advanced evolution, various sources describe traditional RAG as pulling information from a knowledge base to supplement the responses of large language models (LLMs). While Agentic RAG goes a step further by introducing AI Agents that have the freedom to plan, analyze, and iteratively improve data extraction, these resources also highlight the benefits of Agentic RAG such as flexibility, accuracy, and capabilities in adapting to dealing with complex and multi-format datasets, real-world applications, architectures, and challenges associated with their use are also discussed. Overall, these contents explore the concepts, principles, and application aspects of these key AI technologies, highlighting the evolving role of developers in working with these intelligent systems. Track for you: 0:41 Traditional RAG 1:58 The 'Agentic' Leap 2:54 A Team of AI Agents 4:25 Power & Responsibility 5:14 The New AI Toolbox