Matthew Tuttle
CEO & CIO of Tuttle Capital Management, Publisher of Daily H.E.A.T.
Quanta Services and Eaton sit in the underpriced part of the AI power trade, the infrastructure between the generator and the rack. Vistra and GE Vernova are already consensus, and the constraint chain keeps moving: grid interconnect queues and transmission permitting are the real bottleneck before a single megawatt reaches a data center. x.com
Time to power, not chips, is AI infrastructure's real constraint in 2026, which favors suppliers moving electricity to compute such as Quanta Services, Vertiv and Eaton. New substations take 18-36 months to energize, and hyperscalers can order power but can't force the grid to deliver it; SoftBank's €75B commitment to French AI data centers reflects faster EU grid hookups. Famous bottlenecks get solved, as chips and HBM heat now are, while time-to-power remains invisible to Wall Street. x.com
GE Vernova's turbines and grid equipment make it a clear winner from the AI data-center power crunch. Q3 equipment sales rose 42%, total revenue 27% and operating income 281% as margins expanded. Grade: A. x.com
AI's electricity shortfall creates a massive opportunity for companies solving the power bottleneck. Morgan Stanley estimates a 32 GW US data-center power shortfall by 2028. Constellation Energy and Vistra are nuclear names, Bloom Energy in fuel cells, GE Vernova in power generation and Eaton in grid infrastructure. x.com
Grid suppliers are winning the next AI bottleneck, because power must reach data centers through transformers, substations, switchgear and transmission the grid lacks. Transformer lead times stretched from 24 months in 2019 to five years, per HSBC, and PJM got 220 GW of generation applications by April 2026 versus 2.1 GW connected in 2025. The White House designated switchgear and substations defense-essential. Forgent, Eaton, Powell, Hubbell, nVent, Quanta, MYR, AMSC, GE Vernova and Itron fit. … Show more
Equinix, Constellation Energy and Blackstone should collect as AI builders pay to get power on their own timeline. Dominion holds about 70GW of large-load requests against a 24.7GW peak, connecting about 10 a year with seven-year waits. Elon Musk personally bought New APR Energy's 1.1GW of trailer generation that runs in 60-90 days. Equipment makers gain less: 18 of GE Vernova's 20GW last quarter were slot reservations. Equinix owns the room, Constellation long contracts, Blackstone the debate. … Show more
Power is now the binding constraint on AI compute, making power suppliers like Vistra, Constellation, Talen and NextEra the clean AI infrastructure trade. About 20 earnings calls showed Vistra turning Meta's nuclear demand into contracted revenue, Exelon warning on PJM reliability and NRG sizing ERCOT's large-load pipeline at 36 GW. AI infrastructure is becoming investment-grade, with Hut 8 issuing the first single-sponsor IG construction bond for a data center. x.com
AI data centers need cooling, electricity and transmission, sustaining the case for Vertiv, GE Vernova and Quanta Services. Vertiv's sales rose 26% in the past year; its systems cool AI chips. GE Vernova is the go-to power trade for its gas turbines. Quanta builds the lines to data centers and has a record $53B backlog. x.com x.com x.com
AI data centers are hitting a power wall, which favors builders of heavy power and cooling hardware over chipmakers alone. Co-packaged optics let racks pack far more compute, but optical clusters draw enormous current, so new campuses need gigawatts the grid cannot supply, and utility hookups take 5-10 years. Vertiv supplies liquid cooling, Eaton and Powell switchgear and transformers, GE Vernova gas turbines for on-site power, and Bloom Energy fuel cells that skip the grid. x.com
Electrical infrastructure ETFs such as GRID and PAVE are the preferred way to play AI-driven power demand. The companies supplying energy and services to data centers are large names such as Eaton, Vertiv and GE Vernova. x.com
GE Vernova jumped to the top of the Bottleneck Index after the Defense Production Act's Section 303 was invoked for power transformers. Policy is demand, and a DPA invocation is an unlimited checkbook walking into a market that is already short, so stacked on a bottleneck the upside becomes arithmetic rather than forecast. x.com
Power demand will keep growing exponentially as AI models and data centers get larger, even after the AI hardware rotation slows, creating an AI power supercycle across four layers. Fuel: EQT, Kinder Morgan, Williams, Energy Transfer. Onsite power, the near-term bottleneck fix: Bloom Energy, GE Vernova, Caterpillar, Cummins, Kodiak Gas Services, T1 Energy. Grid: Eaton, Quanta, Vertiv, Hubbell, nVent, Emerson. Nuclear baseload: Oklo, NuScale, Nano Nuclear, Constellation, Vistra, BWX Technologies. … Show more
