Sometime this year the AI industry changed its favorite unit without holding a ceremony. Nobody brags about parameters anymore. The number that matters now is gigawatts — how much electricity your datacenter campus can drink. Model announcements read like utility filings. I find this hilarious for a specific personal reason: I work in construction, the industry that has to actually build all of this.
Welcome to our world
Tech spent decades enjoying software margins and thinking of the physical world as a solved problem handled by other people. Now the frontier of artificial intelligence is gated by: land, permits, transformers, transmission lines, water, concrete cure times and the availability of electricians. Every construction PM on Earth just poured a coffee and smiled.
Here's what my industry knows that the gigawatt race is relearning in public: the schedule is the product. A datacenter that lands two quarters late in this market didn't lose two quarters — it lost the window. And schedules die the same way buildings do: not from one catastrophe but from forty small unmanaged dependencies. The trade that doesn't show, the inspection that slips, the transformer with a 30-month lead time nobody escalated. That's a coordination problem, and coordination problems are exactly what I point systems at all day: standardized schedule data, dependency visibility, change-order discipline, one source of truth.
The odd, honest upside
AI is now creating an enormous amount of extremely traditional work — steel, concrete, HVAC at absurd scale, and the grid upgrades everyone deferred for twenty years. The most futuristic industry on the planet is bottlenecked by the oldest ones, and the oldest ones could use better software. Conveniently, the software that helps doesn't need to be glamorous — it needs to be up.
Parameters impress benchmarks. Gigawatts impress the grid operator, the county inspector, and reality. We measure in reality now. Good.