Chapter 1. 99% of Executives Are Misled by AI Advice
As an executive, you’re bombarded with articles and advice on building AI products.
The problem is, a lot of this “advice” comes from other executives who rarely interact with the practitioners actually working with AI. This disconnect leads to misunderstandings, misconceptions, and wasted resources.
A Case Study in Misleading AI Advice
An example of this disconnect in action comes from an interview with Jake Heller, CEO of Casetext.
During the interview, Jake made a statement about AI testing that was widely shared:
One of the things we learned is that after it passes 100 tests, the odds that it will pass a random distribution of 100k user inputs with 100% accuracy is very high. (emphasis added)
This claim was then amplified by influential figures like Jared Friedman and Garry Tan of Y Combinator, reaching countless founders and executives:
The morning after this advice was shared, I received numerous emails from founders asking if they should aim for 100% test-pass rates.
If you’re not hands-on with AI, this advice might sound reasonable. But any practitioner would know it’s deeply flawed.
“Perfect” Is Flawed
In AI, a perfect score is a red flag. This happens when a model has inadvertently been trained on data or prompts that are too similar to tests. Like a student who was given the answers before an exam, the model will ...
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