If 1,000 CS grads found startups attempting to solve a problem they each have, are they guaranteed success? Or will there be five outliers which exit for billions and then tell everyone all they need to do is to solve their own problems?
Telling others to solve a problem they have seems more like an algorithm to generate at least some successes by guaranteeing diversity. This million monkeys approach is a strength of capitalism, but I wonder if it's the method which maximizes expected value for a would be founder. It seems more of a method to guarantee a minimum return for a VC.
Certainly not. Only a fraction of them will have the determination and intelligence required to turn a problem into a startup. And some of those will be unlucky. But more of the 1000 will succeed starting from that rule than any other.
This is not one of those cases where founders and investors' interests are opposed.
It may well maximise expected value for a would-be founder, but that may not map to the founder's implicit utility function. Imagine you have two options:
Option A: 100% chance of receiving $1 billion
Option B: 50% chance of receiving $0; 50% chance of receiving $4 billion
The expected value of A is $1bn. The expected value of B is $2bn. However, most people I know would choose option A, although it has the lower expected value.
Telling others to solve a problem they have seems more like an algorithm to generate at least some successes by guaranteeing diversity. This million monkeys approach is a strength of capitalism, but I wonder if it's the method which maximizes expected value for a would be founder. It seems more of a method to guarantee a minimum return for a VC.