I'm not sure your argument applies only to AI. Intelligence is certainly not knowing through, say, divine inspiration what another person wants you to do. This bottleneck of "describing the problem" is the same bottleneck faced when working with junior (or senior) engineers, especially in a team. One need only consider the classic of our field, Mythical Man-Month, which is really dedicated to this precise and, in some sense, irresolvable problem -- often it's best to just have one person who understands and ideally first posed the problem do the work, rather than introduce this bottleneck of communication.

It's a difficult and crucial problem, we all agree, but it's a stretch to define intelligence as such to be "describing the problem." Choosing the right problem in the first place (i.e. not just telling person B to do X but selecting the X that in fact is worth pursuing), perhaps, but I don't think that's right either as a definition of intelligence. Indeed, even the best scientists often speak of an "intuition" that drives their choice of problems.

More classical definitions place intelligence in the domain of "means-ends rationality", i.e. given an end to pursue being capable of determining the correct way to do so and carrying it out until completion. A calculator like a hammer is certainly not intelligent in that sense, but I would struggle to see how even an AI skeptic could maintain that state-of-the-art LLMs today are not a qualitative step above calculators according to this measure.