Your cart is empty 
In an era where artificial intelligence is transforming enterprises, Large Language Models (LLMs) are unlocking new frontiers in automation, augmentation, and intelligent decision-making. Ultimate Agentic AI with AutoGen for Enterprise Automation bridges the gap between foundational AI concepts and hands-on implementation, empowering professionals to build scalable and intelligent enterprise agents. The book begins with the core principles of LLM agents and gradually moves into advanced topics such as agent architecture, tool integration, memory systems, and context awareness. Readers will learn how to design task-specific agents, apply ethical and security guardrails, and operationalize them using the powerful AutoGen framework. Each chapter includes practical examples—from customer support to internal process automation—ensuring concepts are actionable in real-world settings. By the end of this book, you will have a comprehensive understanding of how to design, develop, deploy, and maintain LLM-powered agents tailored for enterprise needs. Whether you're a developer, data scientist, or enterprise architect, this guide offers a structured path to transform intelligent agent concepts into production-ready solutions. Start building the next generation of enterprise AI agents with AutoGen—today.
Shekhar Agrawal, Senior Director of Data Science at Oracle, is an AI and data engineering expert with over 14 years of experience. He leads the development of Generative AI platforms and enterprise-scale machine learning systems that support thousands of customers worldwide. Known for his technical leadership, he has built robust AI governance frameworks, integrating innovative technologies such as Kubernetes, Spark, and Hadoop. Previously, he held impactful roles at IQVIA, Comcast, and AOL, delivering AI solutions that boosted operational efficiency and user experiences. With a master's degree in electrical and computer science from the University of Cincinnati and a bachelor's in engineering from Birla Institute of Technology, Shekhar blends deep technical expertise with strategic vision to drive innovation in data engineering and AI.
Srinivasa Sunil Chippada is a skilled Data Science Engineering expert with 19 years of experience in building scalable enterprise data systems. He offers valuable technical insights for maximizing data value through Feature Stores, Data Marts, Data pipelines and Data Integration techniques. Passionate about scaling Data Capabilities, he provides strategic technical insights to help organizations implement their data-driven visions. He has a Double Masters (MIS, MBA), is a certified Project Management Professional, and holds several technical Certifications.
Rathish Mohan is a distinguished applied scientist and AI/ML leader with over a decade of experience in machine learning, Natural Language Processing (NLP), and computer vision. He currently serves as a Senior Applied ML Scientist at Lore|Contagious Health, where he leads cross-disciplinary teams to develop advanced AI systems focused on real-time conversational AI and personalization engines, leveraging state-of-the-art technologies such as prefix tuning, LLMs, and RAG pipelines. Previously, Rathish held senior roles at Twitch, OfferUp, and Bold, driving key initiatives such as personalization algorithms, content moderation systems, and recommender engines. He holds a master's degree in electrical engineering from the University of Cincinnati, where his thesis focused on optimizing sensor placement for fault detection using advanced machine learning techniques. With a passion for applying AI to real-world problems, Rathish continues to push the boundaries of AI in health, e-commerce, and user personalization.
Sneak Preview
