My Book on Building Production AI Agents

January 11, 2026

Why This Book Exists

In 2025, AI Agents moved from labs to production. But when you actually try to build an enterprise-ready Agent system, you discover:

  • Most tutorials stop at "call an API to make a chatbot" demos
  • Multi-agent coordination, token budgets, error retry, state persistence—no clear answers
  • Existing frameworks don't meet enterprise needs: security auditing, cost control, observability

This AI Agent Book fills that gap.


What You'll Learn

Part 1-2: Agent Foundations

  • The Essence of Agents — From ReAct to Reasoning + Acting
  • Tool Calling — Function Calling design patterns
  • MCP Protocol — The tool integration standard released late 2024
  • Structured Output — Getting parseable data from LLMs

Part 3-4: Single Agent Deep Dive

  • Memory Systems — Short-term, long-term, and external memory design
  • RAG Integration — Retrieval-Augmented Generation best practices
  • Planning & Execution — Plan-and-Execute patterns
  • Self-Reflection — Teaching agents to self-correct

Part 5-6: Multi-Agent Orchestration

  • Multi-Agent Patterns — Supervisor, Hierarchical, Swarm
  • DAG Orchestration — Workflow design with directed acyclic graphs
  • State Management — Persistence, checkpoints, failure recovery
  • Human-in-the-Loop — Human-AI collaboration patterns

Part 7-8: Production Deployment

  • Cost Control — Token budgets, rate limiting, caching strategies
  • Security & Permissions — Sandboxed execution, audit logs, access control
  • Observability — Tracing, metrics, logging
  • Enterprise Architecture — Evolution from PoC to production

Part 9: Cutting Edge

  • Computer Use — Agents that operate computers
  • Agentic Coding — Code generation agent design
  • Browser Use — Web automation agents
  • Agent Economics — Cost, pricing, and business models

What Makes This Book Different

Patterns Over Frameworks

Every chapter teaches universal design patterns before specific implementations. Frameworks become obsolete; patterns don't.

Battle-Tested Experience

This book comes from building Shannon, a multi-agent platform with a three-tier architecture in Go/Rust/Python.

Covers 2025-2026 Frontiers

MCP protocol, Computer Use, Agentic Coding—these were cutting-edge when I wrote this book.


Who Should Read This

  • Developers building production-grade Agent systems, not just demos
  • Teams handling multi-agent coordination in complex scenarios
  • Engineers concerned with cost control, security, and observability
  • Anyone wanting to understand design patterns behind agent frameworks
  • Backend developers, architects, and technical leads

Available in Multiple Languages

This book is available in three languages:


Start Reading

This book is completely free to read online:

Read the AI Agent Book →


"The best way to learn is to build." This book is a systematic compilation of lessons learned while building the Shannon multi-agent platform.