EDUCATION & TRAINING
How Retrieval-Augmented Generation Actually Works
Dev.to Machine Learning
About This Tutorial
The Two Phases of RAG RAG (Retrieval-Augmented Generation) splits into two separate pipelines: Ingestion pipeline - runs once (or on a schedule) to process your documents Query pipeline - runs live for every user request Why Not Just Send All Your Text to the LLM? Three hard problems: Cost - millions of tokens per query = $$$ Context limits - even 128K token windows can't hold an entire knowledge base Quality - LLMs get confused when buried in irrelevant text RAG surgically extracts only the relevant 3-5 chunks needed for each question.