The 9x Problem Nobody in AI Talks About
In 2006, John Gournville published a paper in Harvard Business Review called “Eager Sellers and Stony Buyers” that should be required reading for every AI founder. His core finding: to get users to switch products, your new thing has to be *nine times better* than what they already use.
Not twice as good. Not “demonstrably superior.” Nine times.
Here’s why. Users overvalue what they already have by a factor of three—the familiarity, the muscle memory, the sense of control. And companies overvalue what they’re offering by a factor of three—because they built it, they know every feature, they see the potential. Three times three equals nine.
This creates what Gournville called a “mismatch of nine to one, or 9x, between what innovators think consumers desire and what consumers really want.”
AI companies act like their next model release will make users switch. They announce benchmark improvements like they’re declaring victory. “Our model is 12% better at coding tasks!” Cool. Is it nine times better? No? Then I’m staying where I am.
Eleganthack
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The 9x Problem Nobody in AI Talks About \ stacker news ~Design
In 2006, John Gournville published a paper in Harvard Business Review called “Eager Sellers and Stony Buyers” that should be required reading f...
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