Thread by @PavelASamsonov

You can't call a feature a solution without first:

1) Establishing the definition of the problem

2) Establishing what it means to solve the problem

Without 1, you get type errors (bake a cake with this hammer).

Without 2, you get scale errors (buy a cake with this penny).

Both a hammer and a penny are features. If you asked users - would you like to have this? - some of them might say yes.

But having these things is not sufficient to solve the problem. The user still does not have a cake.

Even when you know what the problem is, and what it means to solve it, you still don't have a solution.

What you might have is a bet. "Based on our research, we *think* that giving the user money will let them buy a cake." We have to place the bet and see if we were right.

Do we give the user $1 million? Probably not. If it turns out the shop only accepts Bitcoin, we just lost a whole lot of money pursuing the wrong solution!

A smart bet minimizes the risk. Maybe we did research and found that some cakes are $5. We give the user a fiver.

The user goes and buys a slice of cake with the fiver. But it turns out that it's not enough - the slice is too small, the quality is poor, there's not enough frosting.

We were wrong, but we only lost five bucks, and gained a lot of knowledge about the dimensions of the problem.

Because we defined success criteria ahead of time, we can easily analyze whether or not our bet was successful, and place future bets more accurately until the problem is fully solved.