I think there's a reward for finesse too.
As you mentioned, scope definition and constraints play a major role but ensuring that you don't just go for the first slop result but refine it pays off. It helps to have a very clear mental model of feature constraints that doesn't fall prey to scope creep.
There's also a reward for not over thinking it and letting AI bring the solutions to you. The outcomes are better when it's a question, answer, and execution session.