AI Agents on AWS: Beginner's guide to building AI agents on AWS (Paperback or Softback)

Build, scale, and deploy autonomous AI agents on AWS using Bedrock, memory, and multi-agent architectures for real-world systems

Key Features

• Progress from agentic AI concepts to production-ready deployment on AWS
• Design and build AI agents with tools, memory, and orchestration
• Deploy, evaluate, and govern agents using Amazon Bedrock AgentCore
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Build reliable AI agents on AWS and move beyond prototypes with practical guidance. This book helps you design, deploy, and manage agentic systems that reason, use tools, and collaborate to solve real-world tasks.

You start with the foundations of agentic AI, understanding how agents think, act, and interact. Design single-agent systems, extend them with tool and function calling, and add memory for context-aware behavior using Amazon Bedrock and SageMaker AI. You will also use LangGraph and Strands to structure agent workflows.

As you progress, create multi-agent systems and orchestrate workflows where specialized agents collaborate. Learn how MCP and A2A enable communication, interoperability, and modular design across agent ecosystems.

Focus on production readiness by deploying and scaling agents with Bedrock AgentCore, evaluating performance, and implementing observability, monitoring, and governance. By the end, you will be able to design and operate robust AI agent systems on AWS.

What you will learn

• Understand how AI agents think, act, and collaborate
• Design single-agent systems with tools and reasoning
• Build agents on AWS using Bedrock and SageMaker AI
• Add memory for context-aware and adaptive behavior
• Create multi-agent systems and orchestrated workflows
• Use MCP and A2A for agent communication and tools
• Deploy and scale agents for production environments
• Monitor, evaluate, and govern agent performance

Who this book is for

This book is for AI engineers, machine learning engineers, cloud architects, software engineers, and developers who want to build and deploy autonomous AI systems on AWS. It is also well suited for graduate and undergraduate students who want to enter the agentic AI space. Familiarity with Python, APIs, and basic AI/ML concepts is recommended, but the book is designed to make agentic AI accessible to readers who are still building their foundation.

Table of Contents

1. Understanding AI Agents on AWS
2. Building Agents with Tools
3. Agent Memory
4. Advanced Agent Architecture Patterns
5. Agent Communication
6. Production Deployment and Enterprise Integration
7. Evaluation, Observability, and AI Governance

Bunny Kaushik is a Solutions Architect at AWS and a AI/ML specialist who works with world's leading Financial Institutions to build scalable AI systems that deliver measurable business impact. He focuses on AI strategy, governance, and enterprise adoption, helping organizations transition from isolated prototypes to production-ready systems. He is also a published author, speaker, and active mentor to startups and professionals. He specializes in practical AI implementation, helping the next generation of builders navigate the transition from theory to production.

Mona is a Senior AI/ML Specialist Solutions Architect at AWS with over 15 years of experience spanning AI/ML, cloud, and software engineering. She specializes in designing and scaling production-grade AI systems, including LLMs, fine-tuning, inference optimization, and enterprise AI architecture across AWS and Google Cloud. Mona is the author of two bestselling books and is also a published speaker and researcher who has contributed to leading industry conferences and academic work. She actively mentors professionals in AI and cloud.