Show HN: MultiPowerAI – Trust and accountability infrastructure for AI agents

The audit trail design has a subtle failure mode worth designing around: if the agent generates its own receipts, a compromised agent generates false ones. The trail looks complete but proves nothing.

The architecture that holds: the authorization enforcement layer generates the receipt, not the agent. Agent requests authority → enforcement grants or denies → enforcement writes the log. The agent never touches the audit trail directly.

Circuit breakers are interesting. One question: what's the behavioral baseline on first deployment? Novel workflows have no history. If the breaker trips on unfamiliar action sequences, early-stage agents will be noisy. If it doesn't, you have a blind window until the baseline stabilizes.

The consensus API is a nice design signal — model disagreement is itself useful data for high-stakes decisions.

Curious what failure mode you've hit most: authorization layer breaking first, or the audit layer?