Agentic AI Unleashed

Agentic AI represents a paradigm shift in artificial intelligence, moving beyond simple chatbots to autonomous systems that can reason, plan, and execute complex tasks with minimal human intervention. As organizations race to harness this transformative technology, the demand for practical guidance on building production-ready AI agents has never been greater.

This comprehensive guide takes you through the complete journey of agentic AI development. Beginning with foundational concepts and theoretical frameworks, you will explore how large language models serve as cognitive cores for intelligent agents. The book covers essential design patterns, tool integration, and memory systems before diving into engineering practices, including development lifecycle, performance optimization, testing, and observability. You will learn deployment strategies, security considerations, and ethical frameworks essential for responsible AI development. The final chapters showcase real-world enterprise and consumer applications and predict the future evolution of the technology and its use cases.

By the end of this book, you will possess the skills to architect, build, deploy, and maintain sophisticated agentic AI systems. Whether you are developing internal enterprise tools or customer-facing AI products, this guide provides the practical knowledge needed to bring autonomous AI agents from concept to production.

WHAT YOU WILL LEARN
● Architect multi-agent systems using proven design patterns.
● Integrate LLMs as cognitive cores for autonomous agents.
● Build secure tool interfaces and external integrations.
● Deploy and observe agents in production environments.
● Apply ethical frameworks for responsible AI development.
● Optimize agent performance through testing and observability.

WHO THIS BOOK IS FOR
This book targets software developers, students, and engineers building agentic AI products. It serves as a strategic reference for business leaders and executives making investment decisions.

1. Introduction to Agentic Systems
2. Theoretical Frameworks
3. The Agentic Ecosystem
4. Large Language Models as Cognitive Cores
5. Agent Patterns and Design Paradigms
6. Tools and Interfaces
7. Memory Systems
8. Development Lifecycle
9. Performance Optimization
10. Testing and Quality Assurance
11. Monitoring and Observability
12. Deployment Strategies
13. Security and Safety
14. Ethical and Responsible Development
15. Enterprise Applications
16. Consumer Applications
17. Future Directions
18. Example of Conversational Agent

● Jayaram Nanduri is the chief technology officer and co-founder of Truveta, where he oversees all engineering, AI/ML, security, privacy, and compliance. As one of the leaders who coined Truveta's mission, Saving Lives with Data. Jay is passionately driven by the potential of AI to unlock transformative research capabilities through rich EHR data.

Previously, over a 22-year career at Microsoft, Jay rose through the ranks to the prestigious level of Technical Fellow, earning multiple patents and technical publications along the way. He led Microsoft Dynamics 365 Fraud Protection and supply chain insights, championing data gravity through consortiums, AI-driven insights, and global optimization via operations research. He architected cloud-based machine learning and graph platforms that serve as the backbone of Microsoft's product infrastructure, spanning loyalty programs, recommendations, and campaign systems that drive engagement and monetization across major consumer and commercial products. He also played a pivotal role in building the Bing search engine, with key leadership across Bing Mobile and Bing Maps.

Jay holds a master of computer science from the National Institute of Technology India and a master of business administration from The Wharton School.

● Anand Oka is senior VP of AI at Truveta, where he leads the development of AI platforms powering healthcare data harmonization and research applications, including an intelligent network of collaborative AI agents. With over 25 years of experience in AI, cloud, and data platforms, Anand previously held roles at Microsoft across multiple product lines, including Bing Search and Office, fraud protection, and supply chain insights, and at BlackBerry in mobile systems optimization. His first job at an Israeli start-up involved the development of advanced modulation and coding systems for high-throughput wireless communication networks. He is a senior member of IEEE with 20 patents and 18 publications in AI, signal processing, and wireless networks. Anand holds a PhD in electrical and computer engineering from the University of British Columbia, Canada, a Master of Science from the Technion, Israel, and a Bachelor of Engineering from College of Engineering Pune (COEP), India.