As AI agents move from research labs into production, engineering teams face mounting challenges—fragile tools, rising inference costs, erratic behavior, and unmet expectations. AI Agents: The Definitive Guide addresses what most books avoid: how to design, deploy, and maintain real AI agents that actually work in the real world, not just in demos. Written by Nicole Koenigstein, this book offers the practical, system-level foundations needed to build robust, scalable, and secure agentic systems. Whether you're tasked with making agent prototypes production-ready or building mission-critical automation from the ground up, this book guides you through every layer of the stack, without being framework-dependent. It covers architectures, tool integration, performance optimization, safety strategies, and advanced evaluation, with a relentless focus on reliability and long-term value. Design stateful, reasoning, and multi-agent systems Apply reinforcement learning, search, and test-time compute Build reliable tool integration and execution boundaries Evaluate agents across development and production Design memory, monitoring, fallbacks, and efficient infrastructure Secure agents through isolation, governance, and threat modeling
