Gavin Baker, managing partner and CIO of Atreides Management, is calling time on one of the most profitable AI infrastructure trades of the past year. The so-called “bottleneck trade,” built around betting on companies that controlled scarce resources in the AI supply chain, is losing its edge as physical shortages ease.
The bottleneck thesis, explained
The critical chokepoints included TSMC wafer capacity, power generation, cooling systems, optics, and networking equipment. Companies positioned at these bottlenecks could essentially name their price because demand for AI compute far outstripped supply at every level.
Baker offered a striking data point to illustrate just how severe the demand-supply mismatch has been. He estimated that unconstrained Nvidia GPU demand could reach $2-3 trillion annually.
Baker specifically highlighted TSMC’s disciplined approach to wafer capacity as a critical factor. By not flooding the market with supply, TSMC effectively prevented what Baker suggests could have been a full-blown AI bubble.
