AWS Launches Dogwood to Enforce Sequence-Aware Policies for AI Agents

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AWS released Dogwood this week, an open-source policy language licensed under Apache 2.0 that adds temporal, sequence-aware authorization for AI agents. It extends Cedar, AWS's existing stateless authorization language, which can only evaluate individual requests in isolation without knowledge of prior actions. Dogwood addresses this gap by tracking event histories, allowing policies to count in-flight requests, sum transferred values, and verify approvals across a time window before permitting an action. For example, an agent restricted to $5,000 per hour can be properly rate-limited even across concurrent requests that Cedar alone would each approve individually. The reference implementation is available on GitHub for exploration, while production use requires additional infrastructure such as trusted timestamps and durable trace storage; AWS is currently seeking language design feedback rather than code contributions.

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