Introduction
What RAG is, what it isn't, and how to think about the tradeoffs that drive production decisions.
Before diving into implementation details, it's worth getting clear on what you're actually building. RAG is a pattern that sounds simple in a slide deck but turns out to have a lot of surface area in practice. This module establishes the vocabulary and mental models you'll use throughout the rest of the handbook.
By the end of this module, you should be able to explain what RAG does (and doesn't do), sketch the major components of a production system, identify which use cases RAG is well-suited for, and reason about the fundamental tradeoffs between quality, latency, and cost.
Chapters in this module
Chapter 1: What is RAG? defines RAG in operational terms. You'll understand the retrieve-augment-generate pattern, see why teams choose it over alternatives like fine-tuning, and preview the failure modes that make RAG harder than it looks.
Chapter 2: Anatomy of a production RAG system walks through the components you'll need to build: ingestion pipelines, retrieval systems, rerankers, context builders, and the monitoring infrastructure that tells you when things break.
Chapter 3: Use cases and non-goals helps you match RAG patterns to product requirements. Documentation search, support copilots, and internal knowledge assistants have different needs. Knowing what shape your system should take saves you from building the wrong thing well.
Chapter 4: The RAG triangle introduces the core tradeoff that drives most architecture decisions. Quality, latency, and cost pull against each other, and understanding where the knobs are helps you make intentional choices rather than discovering constraints in production.