Comment by sulam

You've just described what the AI industry refers to as "evals", a collection of which forms a particular benchmark. I definitely encourage you to define your own evals, because the public benchmarks are often either saturated (largely solved and only going to see small improvements going forward) or seemingly not predictive of real world performance. I could also go further and speculate that they are in the training data, although credible benchmarks avoid this, I'm just not sure how successful they are.