The RAG Playbook: A Field Guide to Building Reliable AI Systems
by Ryan Grissinger
2025 • 268 pages
About This Book
A practical, framework-driven manual for developers and business leaders on building reliable, grounded AI systems using Retrieval-Augmented Generation. LLMs are powerful but untrustworthy when ungrounded. RAG solves this by coupling retrieval with generation—turning "smart guessers" into truth-based systems. Learn the complete RAG loop: retrieve relevant data, augment queries with context, and generate grounded responses. Master ingestion, chunking, embeddings, evaluation, and governance. Transform hallucinating LLMs into truth-anchored, enterprise-ready assistants people can trust.
The Complete RAG Pipeline
The RAG Loop: Retrieve → Augment → Generate
Everything in this book supports building and optimizing this core loop to turn LLMs from "smart guessers" into grounded, trustworthy systems.
Phase 1-3: Foundation
Data ingestion, preprocessing & chunking, embedding & indexing. Build a clean, searchable semantic knowledge base.
Phase 4-6: The Core Loop
Retrieval, augmentation, and generation. Fetch context, combine with queries, produce grounded answers.
Phase 7-8: Optimization
Evaluation and tuning. Measure accuracy, reduce hallucination, optimize latency and cost.
Phase 9-10: Production
Deployment, scaling, governance & maintenance. Build sustainable, compliant, production-ready systems.
Phase 11: Field Guide
Quick-reference checklists and quick-start playbook. Get started fast, iterate smart.
Key Principles
- ✓ Garbage in, garbage out — quality ingestion determines quality answers
- ✓ Retrieval > Model — fix retrieval before swapping LLMs
- ✓ Prompts = Code — prompt design governs reliability
- ✓ Small chunks, big wins — tune chunk size for semantic precision
- ✓ Trust is the product — reliability beats novelty
This book is free because I believe the best way to elevate the industry is to share what works. If you're building something interesting and need architectural guidance, let's talk.
— Ryan Grissinger