Building Production-Ready Agents with TypeScript, Effect, and Amazon Bedrock

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some courses have accessibility limitations and are working to address. 

• Using the Effect library in TypeScript to manage effects, dependencies, retries, and concurrency in AI agent codebases.
• Integrating Amazon Bedrock APIs (e.g., invoking models like Claude or Llama) within TypeScript-based agents for generative tasks.
• Applying functional programming patterns (e.g., piping, layering, error channels) to create composable and resilient agent behaviors.
• Implementing production considerations such as logging, observability, retry mechanisms, and structured outputs for reliable agent performance.

• Understand how to leverage TypeScript and Effect to structure AI agent logic with strong typing, composability, and robust error handling, reducing common pitfalls in agent development.
• Gain hands-on familiarity with invoking and orchestrating Amazon Bedrock models within agent workflows for tasks like reasoning, tool use, and response generation.
• Feel equipped to start building production-ready generative AI agents that are more predictable, testable, and easier to debug compared to traditional imperative approaches.

• 7-minute concise digital course content with explanations, code examples, and demonstrations focused on TypeScript + Effect + Bedrock agent building.
• Fundamental-level training in the AI/Generative AI domain, suitable for developers familiar with TypeScript looking to advance in agentic AI.
• Practical guidance on modern agent development patterns using open-source Effect library alongside AWS Bedrock services.
• Certificate of completion.