Building Agentic AI Systems

The field of artificial intelligence is undergoing a paradigm shift, moving beyond instruction-based generative AI to intent-driven agentic AI. This new frontier is defined by autonomous systems that can independently reason, plan, and act to achieve complex goals, serving as a strategic imperative that promises to redefine operational efficiency for the modern enterprise.

This book provides a hands-on playbook for architects and technology leaders to move from prototypes to robust, enterprise-grade agentic applications. It guides you through the lifecycle of building autonomous systems, mastering durable patterns like Coordinator-Worker-Delegator (CWD), building for interoperability using the open-standard Agent Communication Protocol (ACP), and mitigating security threats with a formal Agentic Risk Framework.

By the end of this book, you will be equipped with the expert knowledge required to architect, build, deploy, and govern sophisticated, scalable, and value-driven agentic AI systems that deliver tangible results in real-world enterprise environments.

WHAT YOU WILL LEARN
● Architect autonomous AI agents with modern Python frameworks.
● Implement multi-agent workflows using LangGraph and AutoGen.
● Integrate the Model Context Protocol for API tool utilization.
● Manage state and memory in long-running agentic systems.
● Deploy dynamic retrieval-augmented generation (RAG 2.0).
● Establish rigorous security protocols and ethical AI guardrails.
● Scale enterprise AI systems for complex production environments.

WHO THIS BOOK IS FOR
This book is for AI developers, machine learning engineers, software architects, technology leaders, and product managers aiming to build the next generation of autonomous enterprise systems. Readers should have an intermediate understanding of Python and foundational concepts in large language models.

1. From Instruction to Intent
2. Anatomy of an Intelligent Agent
3. Principles of Multi-agent Collaboration
4. Coordinator Worker Delegator Pattern
5. Architecting for Interoperability with the Agent Communication Protocol
6. Modern Agentic Stack and its Decision Framework
7. Evaluating Agent Performance with Business Value Metrics
8. Observability and Debugging for Autonomous Systems
9. Economics of Agency Managing Cost and ROI
10. Architecting Trust with the Agentic Risk Framework
11. Designing for Collaboration with Human-in-the-Loop Patterns
12. Moral Compass of Ethical Frameworks and Accountability
13. Sector Deep Dives in Agentic AI Production
14. Next Frontier in Architecting Self-improving Systems

Ajay Behuria is a technology executive, AI strategist, and inventor with over 25 years of experience driving innovation in the healthcare and retail sectors. As a CEO, founder, and principal AI strategist, he architects large-scale AI transformation programs for major enterprises. Previously, during his extensive career spanning decades at leading global organizations, he progressed to leading technology research and innovation, where he spearheaded award-winning AI initiatives. His career is distinguished by a robust portfolio of patents and a deep expertise in translating complex emerging technologies into measurable business value.