Building GenAI Assistants with AWS Bedrock Agents and Step Functions

Modern operations demand faster resolution times, and generative AI offers a powerful way to automate routine support and remediation tasks. This text-based course guides you through orchestrating intelligent assistants that can take real-world actions. You will learn to build and deploy GenAI assistants by combining AWS Bedrock Agents with AWS Step Functions. By understanding how to link large language models to structured workflows, you will transition from writing simple prompts to deploying autonomous agents that safely interact with your operational systems. What you'll learn: Understand the foundational concepts of generative AI orchestration and agentic workflows; Configure AWS Bedrock Agents to interpret user intent and select appropriate actions; Design AWS Step Functions to orchestrate complex, multi-step remediation processes safely; Apply basic prompt engineering and retrieval-augmented generation (RAG) principles to guide agent behavior; Implement secure integration patterns to connect your AI assistant with external APIs and databases; Monitor and debug serverless AI workflows using modern observability practices. The course begins with core definitions of AI agents and serverless orchestration, then guides you step-by-step through configuring Bedrock Agents, building Step Functions state machines, and connecting them to automate real-world support scenarios. This course is designed for cloud enthusiasts, developers, and operations professionals who are new to generative AI integration and want a practical, step-by-step guide without needing prior machine learning experience. Start building your first autonomous cloud assistant today.