Overview

AI systems don't fail like traditional software. They fail silently, probabilistically, and at scale. Building Secure LLM and AI Applications is the definitive, production-grade guide to guardrails, monitoring, and observability for real-world AI systems. This book goes far beyond theory to show how AI actually breaks in production-and how to prevent, detect, and recover from it. You'll learn how to secure LLM-powered applications against hallucination, prompt injection, data leakage, misuse, drift, and autonomous failure. From prompt engineering as a security control to enterprise-scale AI observability, incident response, governance, and ethics-this book provides end-to-end coverage for modern AI systems. Packed with real-world scenarios, hands-on mini projects, checklists, playbooks, and reference architectures, this is the practical handbook for anyone building or operating AI in production. If you're responsible for trustworthy, secure, and scalable AI, this book is your blueprint.

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