You need to very specific and also question the output if it does something insane

This decade’s version of “works on my box”

I've found it's less about specificity and more about removing the # of critical assumptions it needs to make. Being too specific can be a hindrance in it's own regard.

And that's also a decent barometer for what it's good at. The more amount of critical assumptions AI needs to make, the less likely it is to make good ones.

For instance, when building a heat map, I don't have to get specific at all because the amount of consequential assumptions it needs to make is slim. I don't care or can change the colors, or the label placement.