Reliable Evaluations for LLMs and AI Agents

This book gives practitioners a concrete, systematic framework for designing evals that make AI systems safe, robust, and customer-ready before they reach production. Drawing on real-world failures, from chatbots that went off the rails to shopping assistants that hallucinated product information, it shows how seemingly small evaluation gaps can cascade into legal, financial, and reputational cris...