Building AI Workflows with Bedrock Prompt Flows

As generative AI moves from simple prompts to complex business systems, developers need a structured way to link multiple AI steps together. Managing these multi-step interactions reliably requires robust orchestration tools rather than unpredictable, ad-hoc scripts. This text-based course guides you through the foundational concepts of designing, deploying, and managing deterministic AI workflows using Bedrock Prompt Flows. You will learn to coordinate foundation models, handle data transformation, and integrate external tools to build predictable, production-ready AI systems. What you'll learn: Understand the core architecture of Bedrock Prompt Flows and how to orchestrate multi-step generative AI tasks; Configure inputs, outputs, and intermediate data routing to ensure predictable flow execution; Apply prompt engineering best practices within automated workflows to improve output quality; Integrate retrieval-augmented generation (RAG) patterns to connect foundation models with external data sources; Manage version control, batch processing, and monitoring to trace and optimize workflow performance. The course begins with foundational definitions of AI orchestration and the core components of Bedrock. From there, you will progress through text-based explanations and configuration examples detailing data mapping, conditional routing, and system monitoring. This course is designed for beginners, developers, and cloud enthusiasts looking to build structured AI applications, and no prior experience with AI workflow orchestration is required. Start reading today to build reliable, production-ready AI workflows.