Description Agentic AI is rapidly emerging as the next frontier in artificial intelligence, enabling systems to act autonomously, adapt in real time, and make goal-driven decisions. In todays fast-evolving digital landscape, this technology is reshaping industries by powering intelligent workflows, enhancing efficiency, and unlocking new opportunities for innovation. This book provides a structured journey from foundational concepts to advanced implementation. It begins with the evolution of AI and the defining principles of agentic systems, then explores agent properties such as memory, personas, and lifecycle management. Readers will gain insights into enabling technologies like LLMs and reinforcement learning, followed by architectural patterns for building scalable agents. The chapters provide hands-on evaluations of frameworks like AutoGen, CrewAI, and LangGraph, alongside strategies for data governance and industry-specific use cases in finance and healthcare, such as fraud detection, healthcare personalization, and supply chain optimization. Through a delivery bot case study, you will master implementation, scaling, and AgentOps. Finally, we cover production readiness using containerization and LLM-as-a-judge evaluation to prepare you for the path to AGI. By the end of this book, you will be competent in designing, securing, and deploying professional AI agents. You will possess the practical skills to transition from concept to production, ready to lead innovation in the agentic age. What you will learn Understand core principles that define modern agentic AI systems. Learn step-by-step methods for designing enterprise agent workflows. Discover data foundations needed to enable reliable autonomous agents. Explore architecture patterns for scalable multi-agent applications. Build practical skills to prototype, test, and deploy AI agents. Apply observability and monitoring principles for auditing agent behavior. Identify real industry use cases and implementation best practices. Who this book is for This book is for technology leaders, architects, and developers who possess a solid foundation in Python and basic AI concepts. It serves product teams and practitioners needing professional guidance to design, scale, and responsibly deploy autonomous multi-agent systems. Table of Contents 1. Introduction to Agentic AI 2. Essential Concepts of Agentic AI 3. Core Technologies Enabling Agentic AI 4. Agentic AI Architecture 5. Data Management for Agentic AI 6. Frameworks for Agentic AI-Part 1 7. Frameworks for Agentic AI-Part 2 8. Value Add with Agentic AI 9. Practical Example: Case Study 10. Implementation Approach to Agentic AI 11. Productionizing Agentic AI 12. Future of Agentic AI Glossary Bibliography Further Readings
