Software-based AI capability leaps matter, but the real structural inflection arrives when models integrate with physical robotics to perform manual labor and manufacturing. This physical frontier remains severely neglected in policy discussions despite impending industrial supply chain consequences.
Recent agentic coding tools enable small research teams to conduct data-intensive supply chain modeling that previously required dozens of people. Adopting an AI-forward approach collapses the institutional scale needed to produce technical hundred-page policy reports.
Focusing research on physical elements like chipmaking tools and hardware creates durable insights that do not quickly become obsolete. Supply chain dynamics follow predictable physical laws, allowing researchers to model future geopolitical impacts with fractal detail.
Existing export restrictions left older DUV immersion systems unrestricted, allowing China to double its installed base. Halting all DUV tool flows could cap China's domestic chip production at roughly 10 million chips annually, maintaining a massive US compute advantage.
China will likely struggle to indigenously manufacture commercial DUV immersion lithography tools until the mid-2030s, long after domesticating deposition or etch tools. Because only Japan and the Netherlands produce them, lithography remains the West's most durable geopolitical lever.
Siloing researchers away from legislative engagement degrades both policy advocacy and research prioritization. The original analyst is uniquely qualified to communicate technical nuances to officials and uses those conversations to identify the government's future analytical needs.
AI policy typically divides into a security mindset focused on frontier catastrophic risks and a diffusion mindset focused on institutional economic adaptation. Sustainable policy requires bridging both worldviews, as catastrophic safeguards mean little without answers to human labor substitution and social displacement.