Your AI agent’s next tool call may be valid but wrong. AWS’s Dogwood promises to fix that.
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AWS Dogwood is a novel open-source policy language for AI agent governance, directly relevant to agent orchestration and infrastructure.
AWS open-sourced Dogwood, a policy language and interpreter under Apache 2.0 that governs sequences of AI agent tool calls, extending Cedar's point-in-time authorization with temporal conditions. Dogwood enables policies that check prerequisites, rate limits, and ordering—for example, allowing a stock-trading agent to sell shares only if an approval tool returned positive within the past hour. It is now supported in Amazon Bedrock AgentCore Policy, using Metric First-Order Temporal Logic to evaluate event sequences and parallel calls.