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
This 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.
