Designing AI Agents with AWS Bedrock

Modern AI is shifting from static chat prompts to autonomous agents that can plan, use tools, and execute complex workflows. This text-based course guides you through designing and orchestrating goal-driven AI agents using AWS Bedrock. By reading through detailed explanations, structural breakdowns, and configuration examples, you will understand how to connect foundation models to real-world data and external APIs. You will gain the skills needed to design agents that maintain memory, utilize guardrails, and execute multi-step tasks independently. What you'll learn: - Understand the foundational architecture of autonomous AI agents and how they reason - Configure AWS Bedrock Agents using foundation models to orchestrate complex tasks - Design OpenAPI schemas to connect your agents with external APIs and databases - Apply prompt engineering techniques to define clear agent instructions and boundaries - Implement persistent agent memory and context retention across user interactions - Integrate security guardrails and safety filters to ensure reliable agent behavior You will start with core agent terminology and foundational concepts before moving into action groups, API integrations, and memory management. Through structured text explanations and configuration snippets, you will learn how to design end-to-end agent workflows. This course is designed for beginners, developers, and cloud enthusiasts looking to enter the world of AI orchestration, with no prior experience with AWS Bedrock or agent design required. Start reading today to build your first autonomous AI agent.