AgentCore Launches Agent Performance Loop: Optimization, Batch Eval, User Simulation

Full analysis

AWS AgentCore introduced three capabilities to close the observe-evaluate-optimize-deploy loop for production agents. Optimization analyzes production traces and evaluator outputs to recommend targeted updates to system prompts and tool descriptions, with built-in A/B testing. Batch evaluation replays historical sessions to catch regressions before deployment. User simulation generates realistic multi-turn conversations using LLM-backed (large language model) actors to expose behaviors beyond scripted test cases. Together these features let teams continuously improve agent quality using real production data rather than manual intervention.