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Authoring Dogwood policies from natural language in Amazon Bedrock AgentCore

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AI agents can take actions that do not match your organization's policies. Policy in Amazon Bedrock AgentCore lets teams enforce controls across agents, now including time-based constraints. This post shows how Policy Authoring turns natural-language policy documents into correct Dogwood policies, with worked examples and best practices.

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AI agents can automate complex workflows but might take actions that don’t align with your organization’s policies or regulatory constraints if used without proper controls. To address this, we built Policy in Amazon Bedrock AgentCore so teams can implement controls that are applied across agents running in Amazon Bedrock AgentCore . This was recently expanded with new capabilities for enforcing restrictions that constrain agent actions across time , which support policies such as rate…

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

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Authoring Dogwood policies from natural language in Amazon…