Where the Rerating Moved Next

This course examines how markets identify and price successive economic bottlenecks. It follows a narrative arc from the first recognition of a constraint to the subsequent repricing of the entire supply chain. Using the AI sector as a primary case study, the curriculum tracks the movement of capital from chip designers like Nvidia to manufacturing foundries and specialized high-bandwidth memory suppliers. It details the transition from compute hardware to physical requirements, including data center cooling, power management through companies like Vertiv and Eaton, and the broader grid-scale electrical infrastructure managed by GE Vernova. The series emphasizes second-order thinking to determine where capital flows after the most visible winners have already rerated. The analysis extends beyond technology into baseload energy sources, such as nuclear power and uranium, and the geopolitical scarcity of rare earth materials. Each segment applies a consistent six-part framework to evaluate how shifts in procurement, regulatory access, or technological milestones trigger market reassessments. This involves looking at defense modernization, biotechnology platform optionality in mRNA oncology, and emerging fields like quantum computing and space. The curriculum provides a structured method for identifying underpriced constraints before they become market consensus. It focuses on the specific economic questions that arise when one asset reaches capacity and the market searches for the next scarce input, whether that constraint is a raw material, a manufacturing slot, or a regulatory license.