Day 4: What Is RAG, and What Does It Mean to Make It Agentic?

This article explains Retrieval-Augmented Generation (RAG), a key technique for enterprise AI applications. RAG enhances Large Language Models (LLMs) by retrieving relevant data from internal sources before generating a response, improving accuracy and grounding answers in specific, up-to-date information. While RAG was dominant in 2024, the focus is now shifting towards Agentic RAG, where retrieval isn't a one-time step, but an iterative process within a larger reasoning loop, allowing agents to continuously learn and adapt during complex tasks.