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        <title>Why Off-the-Shelf AI Doesn't Understand Money — Udi Menkes, Intuit</title>
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        <description>Ask a frontier model how to make a rental property more profitable and it will tell you, with total confidence, to raise a good tenant's rent by 5% to 10%. Udi Menkes calls this the fluent bluff: advice that reads perfectly and is quietly wrong, because the model has fluency but no experience. He points to a Princeton study where models handed a million dollars to run a business barely turned a profit, and to his own tests where off the shelf advice would have cost real customers real money. His argument is that context is not experience, and the fix is grounding. At Intuit he turns real business data into millions of state, action, and outcome records, so the model can reason from what companies actually did and what actually followed rather than from a textbook. Tested head to head, the grounded system wins, because it separates advice that sounds right from advice that produced results. The moat, he says, belongs to whoever owns the best system of context in the coming era of outcome driven finance. Speaker info: https://x.com/menkesu, https://www.linkedin.com/in/udimenkes/, https://genaipm.com/about, Timestamps: 0:00 - A three year old's theory of money 2:21 - Why off the shelf models fail at money 2:48 - The rental property example 4:34 - The fluent bluff 6:42 - The Princeton million dollar study 9:45 - Context is not experience 11:03 - Correlation versus causation in pricing 13:37 - Building state, action, outcome data 15:17 - Testing it head to head 16:37 - The era of outcome driven finance 17:55 - Three things to remember</description>
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