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Every essay mourning AI's death of human consultation is describing the product the labs refuse to build. Trust, not truth, is the scarce asset: provenance and positive human-attribution become priced layers once the Granta prize scandal supplies the consumer-grade catalyst. Detection stays a losing arms race; attestation that a human was load-bearing is the durable, unbuilt trade the AI companies keep leaving on the table.
Wong's piece isn't a structural update — every event he cites is recycled public record from the past six months. What's new is that The Atlantic, NYT, Economist, Bloomberg, and Hard Fork have consolidated a unified "AI is no longer compartmentalizable" frame inside 30 days. The Cold War metaphor migration — containment, arms race, geopolitical actors — imports a specific policy menu (export controls, pre-release licensing, technology denial), and Anthropic and OpenAI will IPO into that frame, not the prior permissive one.
Anthropic's run rate doubled from $14B to $30B in two months, the METR study reversed from -20% to +20% developer productivity with current tooling, and some firms are now spending 10% of total engineering labor cost on AI subscriptions: the revenue story is no longer contested. The load-bearing extension claim, MIT's projection that AI completes 80-95% of white-collar tasks by 2029, rests on a linear extrapolation from two data points and an s-curve that doesn't bend. That's the overshoot zone: coding gains are real and documented; legal, marketing, and consulting at the same velocity is a 2027-2028 question, and the piece elides gross margins entirely, which remains the actual bear thesis.
