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 Book Description Cut 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. Who this book is for Developers, 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.
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