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In AI, The Loudest Bottleneck Isn’t Always The Real One

Founders often chase the most visible AI bottleneck—GPUs—while overlooking the real constraints that limit progress. The article argues that true bottlenecks are binding constraints such as power supply, data‑center logistics, or cost‑effective compute sourcing, not necessarily the headline hardware. By defining a clear objective function and mapping constraints, companies can choose the optimal compute strategy—owning GPUs, renting capacity, or partnering—based on what actually blocks their product rollout. This disciplined approach mirrors how the California power market identified batteries, not solar, as the limiting factor.