Building Generative AI Agents - by Tom Taulli & Gaurav Deshmukh (Paperback)

Book Synopsis

The dawn of AI agents is upon us. Tech visionaries like Bill Gates, Andrew Ng, and Vinod Khosla have highlighted the monumental potential of this powerful technology. This book will provide the knowledge and tools necessary to build generative AI agents using the most popular frameworks, such as AutoGen, LangChain, LangGraph, CrewAI, and Haystack.

Recent breakthroughs in large language models have opened up unprecedented possibilities. After years of gradual progress in machine learning and deep learning, we are now witnessing novel approaches capable of understanding, reasoning, and generating content in ways that promise to revolutionize nearly every industry. This platform shift is as significant as the advent of mainframes, PCs, cloud computing, mobile technology, and social media. It's why the world's largest technology companies - like Microsoft, Apple, Google, and Meta - are making enormous investments in this category.

While chatbots like ChatGPT, Claude, and Gemini have demonstrated remarkable potential, the years ahead will see the rise of generative AI agents capable of executing complex tasks on behalf of users. These agents already exhibit capabilities such as running test suites, searching the web for documentation, writing software, answering questions based on vast organized information, and performing intricate web-based tasks across multiple domains. They can autonomously investigate cybersecurity incidents and address complex customer support needs. By integrating skills, knowledge bases, planning frameworks, memory, and feedback loops, these systems can handle many tasks and improve over time.

Building Generative AI Agents serves as a high-quality guide for developers to understand when and where AI agents can be useful, their advantages and disadvantages, and practical advice on designing, building, deploying, and monitoring them.

What You Will Learn

• The foundational concepts, capabilities, and potential of AI agents.
• Recent innovations in large language models that have enabled the development of AI agents.
• How to build AI agents for launching a product, creating a financial plan, handling customer service, and using Retrieval Augmented Generation (RAG).
• Essential frameworks for building generative AI agents, including AutoGen, LangChain, LangGraph, CrewAI, and Haystack.
• Step-by-step guidance on designing, building, and deploying AI agents.
• Insights into the future of AI agents and their potential impact on various industries.

Who This Book Is For

Experienced software developers

From the Back Cover

The dawn of AI agents is upon us. Tech visionaries like Bill Gates, Andrew Ng, and Vinod Khosla have highlighted the monumental potential of this powerful technology. This book will provide the knowledge and tools necessary to build generative AI agents using the most popular frameworks, such as AutoGen, LangChain, LangGraph, CrewAI, and Haystack.

Recent breakthroughs in large language models have opened up unprecedented possibilities. After years of gradual progress in machine learning and deep learning, we are now witnessing novel approaches capable of understanding, reasoning, and generating content in ways that promise to revolutionize nearly every industry. This platform shift is as significant as the advent of mainframes, PCs, cloud computing, mobile technology, and social media. It's why the world's largest technology companies - like Microsoft, Apple, Google, and Meta - are making enormous investments in this category.

While chatbots like ChatGPT, Claude, and Gemini have demonstrated remarkable potential, the years ahead will see the rise of generative AI agents capable of executing complex tasks on behalf of users. These agents already exhibit capabilities such as running test suites, searching the web for documentation, writing software, answering questions based on vast organized information, and performing intricate web-based tasks across multiple domains. They can autonomously investigate cybersecurity incidents and address complex customer support needs. By integrating skills, knowledge bases, planning frameworks, memory, and feedback loops, these systems can handle many tasks and improve over time.

Building Generative AI Agents serves as a high-quality guide for developers to understand when and where AI agents can be useful, their advantages and disadvantages, and practical advice on designing, building, deploying, and monitoring them.

About the Author

Tom Taulli (@ttaulli) is a consultant to various companies, such as Aisera, a venture-backed generative AI startup. He has written several books like AI Basics and Generative AI. Tom has also taught IT courses for UCLA, PluralSight and O'Reilly Media. For these, he has provided lessons in using Python to create deep learning and machine learning models. He has also taught on topics like NLP (Natural Language Processing).

Gaurav Deshmukh is a highly skilled technology leader with over a decade of experience driving transformative software engineering initiatives. Throughout his career, he has held pivotal technical roles at prominent companies such as Guidewire, Cigna, Home Depot, American Agricultural Laboratory (AmAgLab), Tata Exlsi, and Amdocs. Gaurav's expertise encompasses a range of cutting-edge technologies, including cloud computing, cybersecurity, software automation, data engineering, and full-stack development with various programming languages and web technology frameworks. He employs his vast knowledge to create innovative solutions that optimize workflows and drive business growth. Gaurav holds both an MBA and a Master's degree in Computer Science, with a focus on data warehousing and computer vision. He is dedicated to elevating the strategic role of software engineering in delivering business value. As a distinguished leader, Gaurav can be reached at gauravkdeshmukh89@gmail.com to explore transformative technical initiatives.