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The GenAI Patterns Book

29 Production Patterns for Building with Large Language Models

This book is 75% completeLast updated on 2026-04-22
Sangam Pandey

You don't need another "intro to LLMs" tutorial. You need patterns—proven architectural blueprints that tell you exactly when to use RAG vs. fine-tuning, how to build agents that don't spiral, and why your retrieval pipeline returns garbage. This book gives you 29 of them, with architecture diagrams and working Python code. Free. No fluff. No vendor lock-in.

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About the Book

A free, open-access guide to 29 battle-tested design patterns for building production LLM systems. Covers RAG pipelines, AI agents, prompt engineering, routing & orchestration, safety guardrails, evaluation, cost optimization, and memory management with architecture diagrams and working Python code.

This is a Draft / Early Access Edition. Content is actively being refined. Your feedback shapes the final version.

By Sangam Pandey — genaipatterns.dev

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Artificial IntelligenceSoftware Engineering

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About the Author

Sangam Pandey

Sangam Pandey builds AI systems and writes about GenAI design patterns at genaipatterns.dev. The patterns in this book are drawn from real production systems and open-source implementations.

Contents

Table of Contents

Table of Contents

Chapter 01 — Prompting
  • Chain-of-Thought
  • Few-Shot Prompting
  • Prompt Chaining
  • Self-Consistency
  • Prompt Optimization
Chapter 02 — RAG
  • Basic RAG
  • Semantic Indexing
  • Hybrid Retrieval
  • Retrieval Refinement
  • Agentic RAG
  • Deep Search
  • Grounded Generation
Chapter 03 — Agents
  • Tool Calling
  • ReAct Loop
  • Code Execution
  • Plan and Execute
  • Multi-Agent Collaboration
Chapter 04 — Routing & Orchestration
  • Semantic Router
  • Model Router
  • Cascading
Chapter 05 — Safety & Guardrails
  • Guardrails
  • Self-Check
Chapter 06 — Evaluation
  • LLM-as-Judge
  • Reflection
Chapter 07 — Cost & Performance
  • Prompt Caching
  • Inference Optimization
  • Small Language Models
Chapter 08 — Memory & State
  • Conversation Memory
  • Long-Term Memory
Appendix A — Composition Guide

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