Authoring Dogwood policies from natural language in Amazon Bedrock AgentCore
Amazon Web Services Sandesh Swamy
Amazon expanded Policy in Amazon Bedrock AgentCore by adding a new natural-language-to-Dogwood “Policy Authoring” capability that enforces agent action constraints applied in real time by the Dogwood monitor in the AgentCore Gateway. The launch adds temporal and trajectory controls, including restrictions like rate limiting, prerequisites, and sequential ordering of tool calls, with an example rule for limiting refunds to amounts of $2,500 or less during 9:00 AM–5:00 PM UTC. Teams can now import policy documents written in natural language and have them automatically converted into syntactically and semantically correct Dogwood specifications that constrain deployed AI agents.
Why it matters
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.