Artificial intelligence has evolved from experimental models into powerful systems that can reason, generate, and act. This book provides a comprehensive, practical guide to building modern AI applications using foundation models, prompt systems, and agentic architectures. AI Engineering and Agentic AI Systems takes a system-first approach, moving beyond theory to focus on how AI works in real-world environments. It covers the full lifecycle of AI development, from foundational concepts to deployment, monitoring, and optimization. Inside this book, you will learn how to: Understand the evolution of AI from rule-based systems to agentic intelligenceWork with foundation models and large language models effectivelyDesign structured prompts and scalable prompt systemsBuild retrieval-augmented generation (RAG) pipelines for accurate outputsDevelop AI agents capable of planning, reasoning, and tool useArchitect multi-agent systems and autonomous workflowsEvaluate AI systems using practical, real-world metricsDeploy, monitor, and maintain AI applications in productionManage cost, performance, safety, and compliance risksApply AI across business, development, and personal productivityThis book addresses common gaps in existing AI resources by emphasizing end-to-end system design, real-world challenges, and practical implementation strategies. It integrates prompt engineering, system architecture, and agentic AI into a unified framework. Whether you are building your first AI application or scaling complex systems, this guide provides the knowledge needed to design solutions that are reliable, efficient, and aligned with real-world demands.
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