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Key Takeaways The loudest constraint often distracts founders from the real limiting factor.
AI success depends more on infrastructure logistics than headline technologies like GPUs.
Winning founders identify binding constraints and optimize around what actually blocks progress.
If you want a quick lesson in “the bottleneck isn’t always what’s loudest,” look at the California power market.
For years, politicians articulated the need for green energy production. That meant installing renewables like solar and wind, and incentivizing their production via subsidies. But after all of that effort, the evening price in California actually increased.
The reason is subtle, but the summary is that the real bottleneck turned out to be batteries: the ability to save that cheap daytime power and use it at night.
Now take that same mental model and apply it to AI.
Everyone is talking about GPUs. What’s advertised most broadly right now is that companies are building out their own data centers. But if you’re actually trying to build, you’ll keep running into the same question: How should AI companies try to get the power or the compute that they need?
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