Agent Series (7): Knowledge Base Integration — The Right Way for Agents to Use RAG

RAG Meets Agent - It's Than "Giving the LLM a Search Box" Most people encounter RAG in this form: user asks a question → retrieve from a knowledge base → stuff the results into the prompt → LLM generates an answer. That's Pipeline RAG. It works. But it has a fundamental problem - it doesn't think. Pipeline RAG runs retrieval for every question, regardless of whether it's "How much does WonderBot cost?" (genuinely needs the KB) or "How do you average a Python list?" (the LLM already knows). It's like a worker with one tool: no matter what the job is, first make a trip to the warehouse.