Introducing agent quality optimization in AgentCore, now in preview
Amazon AWS AI Blog / 5/5/2026
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Key Points
- Amazon Bedrock AgentCore introduces agent quality optimization in preview to address performance drift in production as models and user behavior change.
- The new “recommendations” capability analyzes production traces and evaluation outputs to suggest improvements to system prompts or tool descriptions tailored to a chosen evaluator.
- Teams can validate recommendations using batch evaluation against a predefined test dataset to detect regressions in important scenarios.
- For broader coverage, AgentCore can simulate test datasets with an LLM-based actor and run controlled A/B testing to compare agent versions before shipping.
Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evolve, user behavior shifts, and prompts get reused in new contexts they were never designed for. Agent quality quietly degrades. In most teams, the improvement […]
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