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100 Gigawatts to 400. The Biggest Nuclear Bet in American History.

AI data centers need round-the-clock power. Nuclear is the answer everyone keeps arriving at. But the ghost of Vogtle — $30 billion, seven years late — hangs over all of it.

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In June we covered data center infrastructure — the cooling systems, the transformers, the power draw of the AI boom. We left one question hanging: where does all that electricity come from? A single large AI data center can consume as much power as a small city. Solar and wind are intermittent. Natural gas emits carbon. The answer everyone keeps arriving at is nuclear.

Nuclear provides baseload power — constant, reliable, carbon-free, 24 hours a day. It doesn’t care if the sun is shining or the wind is blowing. For a data center that must run every second of every day, that reliability is worth a premium. And after decades of stagnation, the U.S. is finally building again.

The sector splits into four layers. Understanding them is how you understand the opportunity.

The utilities. Companies like Constellation Energy operate the existing reactor fleet. They’re signing power deals directly with tech companies. This is the lowest-risk way to play nuclear — these plants already exist and already generate cash.

The SMR developers. Small Modular Reactors are the innovation story. Factory-built, scalable, potentially cheaper and faster than giant custom plants. NuScale is the only publicly traded pure-play with an NRC-certified design. GE Vernova Hitachi’s BWRX-300 anchors the $40 billion Japan partnership. These are high-risk, high-reward — most are pre-revenue.

The fuel and the builders. Uranium miners supply the fuel — no uranium, no reactors. And the component manufacturers build the hardware. We’ve already covered one: BWX Technologies, which makes reactor components and is expanding into commercial SMRs. GE Vernova, which we covered in June, is a key reactor supplier.

Every nuclear bull case has to answer for Vogtle. The two new reactors at Plant Vogtle in Georgia were supposed to cost $14 billion and open in 2016 and 2017. They ended up costing over $30 billion and opened years late. The overruns pushed Westinghouse into bankruptcy. They were the first new U.S. reactors in decades — and a cautionary tale.

The SMR thesis is a direct response to Vogtle. The problem with big reactors is that every one is custom-built, so mistakes compound. Small modular reactors trade scale for replicability. Build the same unit over and over in a factory, and costs could fall up to 70%, the DOE estimates. That’s the bet. It has not yet been proven at commercial scale in America.

The bull case is demand. AI power consumption is exploding, and nuclear is the only carbon-free source that runs around the clock. Government policy is aligned, capital is flowing, and tech companies are signing long-term power deals. For utilities operating existing plants, that demand is already translating into higher revenue and premium pricing.

The bear case is history. Nuclear has promised a renaissance before and delivered Vogtle. SMRs are unproven at commercial scale. Most pure-play developers are pre-revenue and burning cash. And even the largest tech investments so far are a fraction of what building new plants actually costs. The Bulletin of the Atomic Scientists argues the hype has outrun the reality — SMRs can’t fill the AI power gap in the near term.

Here’s how I’d frame it. The safest exposure is the existing fleet and the proven suppliers. Utilities like Constellation and component makers like BWXT and GE Vernova — both of which we’ve already covered. The pure-play SMR names are lottery tickets: enormous upside if the technology works, total loss if it doesn’t. Nuclear is the clearest example in this newsletter of a sector where the demand is undeniable but the execution is everything. America decided nuclear matters again. Whether it can build without another Vogtle is the $400 billion question.

This issue is for informational purposes only and does not constitute financial advice. Always do your own research before you invest.

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