This course teaches learners how to design AI agents that are trustworthy enough for production use. Using a customer service agent example built on AWS, learners explore the major ways agents fail in real-world environments and the architectural patterns used to reduce those risks.
The course covers agent harness design, layered guardrails, steering, tool safety, policy enforcement, evaluations, observability, and cost controls. By the end of the course, learners will be able to explain and apply practical mitigation techniques for deploying safer AI agents with AWS services such as Amazon Bedrock, Strands Agents SDK, Agent Runtime, Agent Gateway, Lambda, and AgentCore policy.
