Generative AI at AWS: Turn business strategy into production-ready AI applications and agents

About the Book

Bridge business goals and technical execution to build, deploy, and govern generative AI solutions on AWS Key Features Align business strategy with practical generative AI use cases on AWS Build MVPs, agents, and production systems with Bedrock and SageMaker Apply governance, scaling, and responsible AI practices across industries Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionCut through the noise around generative AI and learn how to turn promising ideas into secure, scalable solutions on AWS. This book helps you connect business priorities with technical execution, so you can identify worthwhile use cases, select the right models and services, and move from pilot to production with confidence. You explore the fundamentals of generative AI, understand how foundation models and agents work, and see where services such as Amazon Bedrock AgentCore and Amazon SageMaker AI fit into a modern AI stack. From there, the book guides you through preparing data, building an MVP, deploying production-ready applications, and designing for scalability, governance, and responsible AI. Real-world industry examples and practical decision frameworks help you evaluate when to use generative AI, when traditional approaches are a better fit, and how to measure business value. You also examine advanced topics such as agentic AI, emerging patterns, and the future direction of enterprise AI. By the end of this book, you will be able to plan, build, and govern generative AI solutions on AWS that deliver measurable value for your organization. What you will learn Understand how generative AI creates business value Compare models, prompts, fine-tuning, and RAG Navigate the AWS generative AI stack with confidence Prepare data and select models for real use cases Build MVPs and production-ready AI applications Apply governance, ethics, and responsible AI controls Evaluate agentic AI patterns and emerging trends Measure impact across enterprise AI initiatives Who this book is forDevelopers, solutions architects, technical product managers, innovation leaders, CTOs, and business decision-makers who want to plan, build, and scale generative AI solutions on AWS. It is ideal for teams moving from experimentation to production and for leaders aligning AI initiatives with business outcomes. A basic understanding of cloud concepts and software delivery is helpful.

Table of Contents:
Table of Contents

1. The Generative AI Revolution – Why It Matters Now
2. How Generative AI Works
3. The AWS Generative AI Stack – Tools of the Trade
4. Data Readiness and Model Selections
5. Build an Agentic GenAI Application
6. Production-Ready Agentic & GenAI Applications
7. Advanced Techniques and Emerging Trends
8. From Strategy to Use Case – Identifying Business Value
9. Industry Spotlights and Case Studies
10. Governance Ethics and Responsible AI
11. Empowering People, Teams, and Culture in the Age of GenAI
12. The Future of Generative AI

About the Author :
Nestor Gandara is a technology leader with over 20 years of IT experience specializing in Generative AI, cloud, and digital transformation. As Principal Partner SA and Generative AI Strategist at Amazon Web Services, he partners with C-suite executives to bridge the gap between technology and business value. Nestor is a program lead, mentor, and learning facilitator for MIT Professional Education and a faculty member at IENYC and ISDI. As the Founder of NextLevelguru and author of "The Art of Building Your Resilience and Adaptability," by combining executive leadership with talent mentoring, he holds a unique position at the intersection of Next-Gen Enterprise technology, education, and business strategy. Eduardo Ordax is a Principal GenAI Go-to-Market Lead at AWS with 15+ years of experience across technology, combining technical and business leadership with a strong passion for AI. Recognized as the #1 AI influential voice in Spain and among the #Top20 worldwide, I'm an international keynote speaker and postgraduate lecturer. I actively share insights on AI innovation, strategy, and real-world adoption with a community of 200,000+ professionals on LinkedIn, contributing to shaping the future of artificial intelligence. Srikanth Daggumalli is a Senior Analytics & AI Specialist Solutions Architect at Amazon Web Services, specializing in generative AI, machine learning, and cloud-native data architectures. With nearly two decades of experience, he has architected mission-critical data platforms across financial services, insurance, retail, automotive, ISV, and digital-native sectors, spanning global payments, anti-money laundering, credit-risk management, and enterprise analytics for Fortune 500 organizations. He is an IEEE Senior Member, IETE Fellow, and Technical Program Committee member and peer reviewer for IEEE conferences and Manning Publications. His articles on InfoQ and the AWS Big Data Blog have been syndicated across more than 15 international platforms. Ashutosh Dubey is a technology leader and recognized expert in Generative and Agentic AI at Amazon Web Services. He empowers enterprise leaders to operationalize artificial intelligence at a global scale. A dedicated advocate for technical education and community engagement, he regularly shares industry insights through his public blogs. He is the coauthor of Generative AI for Software Developers and Interview Guide for Solution Architects, providing practical guidance for engineering and leadership teams navigating the complexities of modern software design.