AI Engineering and AI Agentic Systems

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 intelligence
• Work with foundation models and large language models effectively
• Design structured prompts and scalable prompt systems
• Build retrieval-augmented generation (RAG) pipelines for accurate outputs
• Develop AI agents capable of planning, reasoning, and tool use
• Architect multi-agent systems and autonomous workflows
• Evaluate AI systems using practical, real-world metrics
• Deploy, monitor, and maintain AI applications in production
• Manage cost, performance, safety, and compliance risks
• Apply AI across business, development, and personal productivity