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Optimizing agent system prompts with Amazon Bedrock AgentCore

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AgentCore optimization turns production traces into proposed configuration changes, then validates them before promotion. This technical companion to the launch post explains how the system prompt optimizer's reflector engine works and shares benchmark results for the Single Agent and Sub-Agent Reflectors.

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In a previous launch post , we introduced AgentCore optimization, a capability of Amazon Bedrock AgentCore that can help you improve the quality of your agents. Improving a low-scoring agent has traditionally been a manual process. You review long traces to find where the agent goes wrong, tune individual components such as prompts, tool descriptions, and skills, and rerun evaluations to check for improvement. With AgentCore optimization, you can use production traces to propose configuration…

overfeed.news indexa y enlaza. Publicamos un extracto breve; el artículo completo sigue en AWS Machine Learning Blog.

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