finelybook
The Generative AI Career Masterplan: Navigate the future of AI with practical insights from industry pioneers at AI-first organizations
Author(s): Dr. Ali Arsanjani (Author), Sadid Hasan (Author), Maxime Labonne (Author), Andreas Horn (Author), Leonid Kuligin (Author)
- Publisher Finelybook 出版社: Packt Publishing
- Publication Date 出版日期: July 31, 2026
- Edition 版本: 1st
- Language 语言: English
- Print length 页数: 338 pages
- ISBN-10: 1806691450
- ISBN-13: 9781806691456
Book Description
Kick-start your agentic AI career with insights from leaders at Google, Microsoft, and Liquid AI. Learn the skills, strategies, and tools to build intelligent agents, transition faster, and lead in the era of autonomous systems.
Key Features
- Discover the only comprehensive career roadmap for the Generative AI era
- Learn directly from top industry experts, leaders, and AI innovators
- Build future-proof skills, from prompt engineering to ethical AI strategy
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
This book is a landmark publication, the first-ever collaborative guide authored by a powerhouse lineup of industry leaders from Google, Microsoft, IBM and Liquid AI. This all-in-one resource demystifies the Agentic AI revolution and delivers a practical, career-centered framework for every professional, from graduates to senior executives.
You’ll start by understanding Gen AI’s impact on the job market and decoding core concepts like LLMs, transformers, and prompt engineering. With detailed role descriptions and leveling matrices to identify and build a roadmap tailored to your background.
Next, dive into the Gen AI tech stack: RAG architectures, vector databases, function calling, multi-agent systems, and LLMOps. Explore essential frameworks including LangChain, LlamaIndex, Haystack, & Hugging Face, learning when and how to apply each tool effectively. Beyond technical skills, you’ll cultivate the human advantages AI cannot replicate, critical thinking, adaptability, creativity, and ethical judgment. Real-world use cases span finance, healthcare, software development, and marketing, demonstrating how Gen AI transforms industries.
More than a technical guide, this is a career transformation blueprint. It integrates practical frameworks for skill development, job search strategies, and personal branding in an AI-augmented world.
What you will learn
- Understand the global impact of Generative and Agentic AI on jobs and industries
- Master key GenAI & Agentic AI concepts for any professional background
- Identify your best-fit AI career path and transferable skills
- Build familiarity with LlamaIndex, Haystack, Hugging Face, and core RAG workflows
- Build an AI-enhanced personal brand using the 5-Layer LinkedIn Strategy and Portfolio Showcase Framework
- Apply ethical and responsible AI principles and governance in real-world practice
- Create a lifelong learning and upskilling roadmap for sustained growth
Who this book is for
This book is for graduates, professionals, and leaders seeking to future-proof their careers and capitalize on the rise of Generative AI. Whether you’re entering the job market, transitioning from a traditional tech or non-tech role, or aiming to lead AI transformation, this guide provides the clarity, tools, and confidence to take control of your trajectory. It’s an indispensable resource for engineers, data scientists, product managers, business analysts, educators, and executives determined to stay relevant in the new world of work.
Table of Contents
- Generative AI – Revolutionizing the Future of Work, Strategy, and the Global Economy
- Decoding GenAI – Core Concepts for Every Professional
- Mapping Your Path – Roles and Roadmaps in GenAI
- Generative AI Architectures and Advanced Concepts
- Essential Tools and Platforms
- Mastering Hard Skills – The Technical Edge
- Cultivating Technical and Human Skills for the Agentic AI Era
- Strategic Career Moves: Entry, Transition, and Upskilling
- Applied Generative AI: Industry Use Cases and Multi-Agent Systems
(N.B. Please use the Read Sample option to see further chapters)
Editorial Reviews
Editorial Reviews
Review
Leonid Kuligin is a staff AI engineer at Google Cloud, working on generative AI and classical machine learning solutions (such as agentic AI, demand forecasting, and optimization problems). Leonid is also an associate researcher at TUM University Hospital, Technical University of Munich. With over two decades of experience, Leonid has a track record of building B2C and B2B applications and solving users’ problems in domains such as search, maps, knowledge extraction, and investment management in industry-leading German and Russian technological, financial, and retail companies.
About the Author
Dr. Ali Arsanjani is a pre-eminent technical executive who bridges architectural rigor and large-scale organizational strategy with industrial-scale execution. Widely recognized as the “father of SOA”, he has led transformational initiatives across multiple organizations. He currently serves as Director of Applied AI Engineering at Google Cloud, where he leads the GenAI Blackbelts, a center of excellence that bridges research, forward-deployed engineering, and enterprise implementation. In this role, he drives strategic co-engineering programs with Google’s most critical customers and partners, accelerating enterprise adoption of generative AI and agentic AI.
Sadid Hasan, Ph.D., is a Principal AI Leader in the Microsoft AI Development Acceleration Program within the Office of the CTO, where he drives enterprise-scale research and development of advanced generative and agentic AI for Office Copilots and Azure AIOps. With more than 20 years of experience in AI research and innovation, he has led groundbreaking work in generative AI, natural language processing, and machine learning, authoring hundreds of peer-reviewed publications and patents. Before Microsoft, he held AI leadership roles at CVS Health and Philips Research. He is a recognized thought leader, frequent keynote speaker, and was recently named one of the 100 most influential AI leaders in the United States.
Maxime Labonne is Head of Post-Training at Liquid AI. He holds a Ph.D. in Machine Learning from the Polytechnic Institute of Paris and is a Google Developer Expert in AI/ML. He has made significant contributions to the open-source community, including the LLM Course, tutorials on fine-tuning, tools such as LLM AutoEval, and best-in-class models such as NeuralDaredevil. He is the author of the best-selling books LLM Engineer’s Handbook and Hands-On Graph Neural Networks Using Python.
Andreas Horn is an enterprise AI and automation leader with over a decade of experience helping organizations turn emerging technology into practical, scalable operating capability. He has worked with leading technology companies, including IBM and Microsoft, and advised large enterprises on redesigning operations around AI, automation, and resilience. Andreas focuses on moving AI beyond experimentation into measurable, reliable, production-ready use. He advises senior leaders on enterprise AI adoption, speaks on AI-powered operations and organizational change, teaches AI and innovation at universities, and helps organizations build lasting AI capability grounded in real production environments. He mentors professionals and future leaders.
Leonid Kuligin is a Staff AI Engineer at Google Cloud, working on generative AI and classical machine learning solutions, including agentic AI, demand forecasting, and optimization problems. He is also an Associate Researcher at TUM University Hospital, Technical University of Munich. With over two decades of experience, Leonid has a proven track record of building B2C and B2B applications and solving users’ problems across domains such as search, maps, knowledge extraction, and investment management for leading German and Russian technology, financial services, and retail companies.
