The AI Energy Stack: The Actual Industry Winners

July 1, 2026

AI Summary

5 min read

For three years, the AI trade was simple: buy the chips. NVIDIA became the most valuable company on earth by making them. But that thesis has become overcrowded, not because AI is slowing down, but because a new problem has surfaced: no one can turn these GPUs on. Trillions of dollars are being spent, and GPUs are collecting dust in data centers. The bottleneck is energy—the electrical grids, wiring, transformers, and weather infrastructure that keeps a chip alive. The lead time to get power to a new data center in the US is five years. As one host put it, "a token is really just what is output. And that is just a series of electrons flowing through chips, light flowing through fiber, and then heat being pulled out of the system." This episode walks through four companies positioned to solve that bottleneck.

The Energy Bottleneck: Why Power Is the New Constraint

The AI trade has moved from GPUs to semiconductors to memory, and now to what the hosts call "the end game bottleneck": energy. US data center power demand is projected to roughly double from 80 gigawatts in 2026 to 150 by 2028. The grid simply isn't built for that. And the lead time is brutal: if you want to build a data center in the US today, getting the necessary power takes five years. Wiring and transformers alone require custom design and delivery that takes years.

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What you'll learn

1 (00:00) **The Energy Bottleneck Thesis** - The AI trade has shifted from buying chips to solving the power and infrastructure problem that keeps GPUs offline.
2 (01:25) **The Money Cycle Flows to Energy** - Capital is moving from GPUs to the energy bottleneck as data center power demand is projected to nearly double.
3 (02:49) **The 10% Cost That Is 100% of the Bottleneck** - Only 10% of a data center budget goes to power and infrastructure, yet it is the main constraint.
4 (04:50) **Bloom Energy: Modular Fuel Cells for Immediate Power** - Bloom Energy solves the lead-time problem by deploying modular fuel cells on-site in 90 days instead of 3-5 years.
5 (09:54) **Lumentum: Moving Data as Light** - As data centers grow, copper wiring overheats; optical fibers using light become the solution for inter-GPU communication.
6 (13:48) **The Joules-Per-Bit Metric and the Future of Fiber** - Light wins decisively on energy cost per bit transferred, and fiber optics may even enable data storage in transit.
7 (17:27) **Marvell: Designing the Power Delivery on the Chip** - Marvell specializes in the chip design that determines how power is dispersed within and between chips, a critical bottleneck.

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Show Notes

This is the long-awaited Energy Stack episode. The AI trade is shifting from GPUs to the power, wiring, and data center infrastructure needed to support them.

Today, we cover Bloom Energy, optical networking companies like Lumentum and Corning, Marvell’s role in AI hardware, and neocloud providers such as Nebius, CoreWeave, and IREN.

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TIMESTAMPS

0:00 GPU Bottleneck Shifts
0:37 Power Becomes the Constraint
3:15 Five-Year Grid Delays
5:47 Bloom’s Fast Energy Fix
9:54 Data Transfer Hits Limits
11:51 Light Replaces Copper
17:25 Power Delivery Gets Harder
18:22 Marvell Wins Power Design
20:35 Renting Compute at Scale
21:08 Nebius and NeoClouds
25:17 Compute Becomes an Asset
29:47 The Substrate Layer Ahead

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RESOURCES

Josh: https://x.com/JoshKale

Ejaaz: https://x.com/cryptopunk7213

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Not financial or tax advice. See our investment disclosures here:
https://www.bankless.com/disclosures⁠

Josh works with Anthropic as a contractor. All views expressed are his own and do not represent Anthropic, its leadership, or its affiliates. Nothing in this episode is investment advice.