Build AI Agents with SageMaker and MLflow

This post details building AI agents using the Strands Agents SDK, leveraging models deployed on SageMaker AI endpoints. It guides users through deploying foundation models from SageMaker JumpStart, integrating them with Strands Agents, and implementing production-grade observability via SageMaker Serverless MLflow for agent tracing. The guide also covers A/B testing different model variants and evaluating agent performance using MLflow metrics, empowering users to construct, deploy, and enhance AI agents on their own controlled infrastructure.