Building Gen AI Applications with Amazon Bedrock:

Description

Design, Build, and Scale Generative AI Solutions with Amazon Bedrock—End to End

Book Description
Amazon Bedrock enables you to build powerful generative AI applications on AWS without managing infrastructure. This book, Building Gen AI Applications with Amazon Bedrock, is a practical guide to creating production-grade GenAI systems, from your first model invocation to applications that are secure, observable, and cost-aware.

You will learn how foundation models fit into modern software engineering, and how to design solutions such as chatbots, summarization tools, image generation, and personalized experiences—without disrupting your existing stack. As you progress, you will discover how to select and evaluate models, decide when to use prompting, RAG, or agents, and design workflows that perform reliably under real-world conditions.

You will also integrate Bedrock into existing architectures, implement guardrails and evaluation loops, and scale confidently without performance or cost surprises. Working with models such as Anthropic Claude and Amazon Titan will enable you to see how disciplined engineering turns generative AI from a demo into dependable business value. Thus, by the end, you will be ready to build and operate GenAI systems on Bedrock with clarity!

What you will learn
● Build production-ready generative AI applications on Amazon Bedrock.
● Select, evaluate, and compare foundation models with confidence.
● Design robust prompts, structured outputs, and tool integrations.
● Implement RAG pipelines with grounded, verifiable responses.
● Develop agentic workflows with guardrails and safety controls.
● Scale GenAI systems with monitoring, evaluation, and cost discipline.

Who is This Book For?
This book is tailored for software engineers, solution architects, data scientists, ML engineers, DevOps engineers, and technical managers building generative AI applications on AWS. It is ideal for professionals integrating LLMs, RAG pipelines, and AI agents into production systems using Amazon Bedrock. A basic understanding of AWS services, cloud architecture, and modern application development is recommended, but no prior experience in deep learning research or model training is required.