Ashutosh Dubey – författare

Bridge business goals and technical execution to build, deploy, and govern generative AI solutions on AWSKey FeaturesAlign business strategy with practical generative AI use cases on AWSBuild MVPs, agents, and production systems with Bedrock and SageMakerApply governance, scaling, and responsible AI practices across industriesPurchase of the print or Kindle book includes a free PDF eBookBook 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 learnUnderstand how generative AI creates business valueCompare models, prompts, fine-tuning, and RAGNavigate the AWS generative AI stack with confidencePrepare data and select models for real use casesBuild MVPs and production-ready AI applicationsApply governance, ethics, and responsible AI controlsEvaluate agentic AI patterns and emerging trendsMeasure impact across enterprise AI initiativesWho 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.

Bridge business goals and technical execution to build, deploy, and govern generative AI solutions on AWSKey FeaturesAlign business strategy with practical generative AI use cases on AWSBuild MVPs, agents, and production systems with Bedrock and SageMakerApply governance, scaling, and responsible AI practices across industriesPurchase of the print or Kindle book includes a free PDF eBookBook 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 learnUnderstand how generative AI creates business valueCompare models, prompts, fine-tuning, and RAGNavigate the AWS generative AI stack with confidencePrepare data and select models for real use casesBuild MVPs and production-ready AI applicationsApply governance, ethics, and responsible AI controlsEvaluate agentic AI patterns and emerging trendsMeasure impact across enterprise AI initiativesWho 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.

Master Generative AI in software development with hands-on guidance, from coding and debugging to testing and deployment, using GitHub Copilot, Amazon Q Developer, and OpenAI APIs to build scalable, AI-powered applicationsKey FeaturesHands-on guidance for mastering AI-powered coding, debugging, and deployment with real-world examplesComprehensive coverage of GenAI concepts, prompt engineering, fine-tuning, and SDLC integrationPractical strategies for architecting and scaling production-ready AI-driven applicationsBook DescriptionGenerative AI for Software Developers is your practical guide to mastering AI-powered development and staying ahead in a fast-changing industry. Through a structured, hands-on approach, this book helps you understand, implement, and optimize Generative AI in modern software engineering. From AI-assisted coding, debugging, and documentation to testing, deployment, and system design, it equips you with the skills to integrate AI seamlessly into your workflows. You ll work with tools such as GitHub Copilot, Amazon Q Developer, and OpenAI APIs while learning strategies for prompt engineering, fine-tuning, and building scalable AI-powered applications. Featuring real-world use cases, best practices, and expert insights, this book bridges the gap between experimenting with AI and production deployment. Whether you re an aspiring AI developer, experienced engineer, or solutions architect, this guide gives you the clarity, confidence, and tactical knowledge to thrive in the GenAI-driven future of software development. Armed with these insights, you ll be ready to build, integrate, and scale intelligent solutions that enhance every stage of the software development lifecycle.What you will learnBuild a secure GenAI application with expert guidanceUnderstand the fundamentals of GenAI and its applications in software engineeringAutomate coding tasks with tools like GitHub Copilot, Amazon Q Developer, and OpenAI APIsApply AI for debugging, testing, documentation, and deployment workflowsGet to grips with prompt engineering and fine-tuning techniques to optimize AI outputsImplement best practices for architecting and scaling AI-powered applicationsBuild end-to-end GenAI projects, moving from experimentation to productionWho this book is forThis book is for software developers, engineers, architects, and tech professionals who want to understand the core concepts of Generative AI and its real-world applications, master AI-driven development workflows to improve efficiency and code quality, and leverage tools like GitHub Copilot, Amazon Q Developer, and OpenAI APIs to automate coding tasks.