What happens when your software stops waiting for instructions and starts making its own decisions? It searches, writes, books, and acts. Then one day it does something you never expected, and you cannot explain why. If that thought makes you uneasy, this book was written for you. Building an AI agent demo takes an afternoon. Building one you can trust with real customers and real consequences takes engineering. Agentic AI Engineering closes that gap with a clear, practical path from first idea to dependable production system. No hype. No wall of jargon. Just straight talk about how agents really work, why they fail, and how to fix them. Across 30 focused chapters, you will learn how to: Design agents with clear instructions, smart tools, and memory that actually worksBuild your first working agent in one afternoon, then connect it to real data and servicesTest systems that never answer the same way twice, and catch hallucinations before your users doOperate with tracing, cost control, guardrails, and recovery plans for when things breakDefend against prompt injection and other ways agents get hijackedDecide when you need an agent at all, and when a simpler workflow winsImagine opening a trace and seeing exactly why your agent made a choice. Imagine changing an instruction and knowing within minutes whether it helped. Imagine answering "Can we trust this system?" with evidence instead of crossed fingers. That confidence comes from method, not luck, and this book hands you that method. Perfect for: Software developers and engineersData and machine learning professionalsTechnical leads, architects, and product managersFounders building AI-powered productsYou do not need a research background. You need curiosity and a willingness to build carefully. The teams that thrive will not simply use agents. They will engineer them with care, test them with discipline, and operate them with confidence. Scroll up and click "Buy Now" to start building AI agents you can trust today.
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