I agree that the necessity to design complex edge cases to find AI reasoning weaknesses indicates how far their capabilities have come. However, from a different point of view, failures of these types of edge cases which can be solved via "common-sense" also indicate how far AI has yet to go. These edge cases (e.g. blood pressure or car wash scenario) despite being somewhat construed are still “common-sense” in that an average human (or med student in the blood pressure scenario) can reason through them with little effort. AI struggling on these tasks indicates weaknesses in their reasoning, e.g. their limited generalization abilities.

The simulator or world-model approach is being investigated. To your point, textual questions alone do not provide adequate coverage to assess real-world reasoning.