The scenario exhibits high sensitivity to parameter changes: small modifications to assumptions about AI capability, timeline, or lab decision-making lead to drastically different outcomes; this robustness issue argues for classical liberal governance structures (transparency, decentralization) that perform reasonably across many scenarios rather than policies optimized for one specific path.