Although there are several representativeness-based models of the Lawyer-Engineer task, it remains unclear just why people rely on representativeness-based heuristics rather than on posterior probabilities. This is especially striking because subjects have access to the rational answer: irrational answers decrease dramatically in frequency formats (Gigerenzer&Hoffrage,1995). We argue that the availability of representativeness is explained by the fact that subjects (1) engage in question-answering behavior, as predicted by theories of linguistic semantics, and (2) recursively reason on each other’s mental states, as predicted by the Rational Speech Act Theory (Frank&Goodman,2012). To test this, in a norming study, we asked participants for frequency judgments on the components of Bayes' law, using pairs of real-world professions and related descriptions. In the main experiment, an independent group gave probability judgments on lawyers-engineers problems. We compared different models built from the normed values, and found that those incorporating (1) and (2) best predicted main-experiment responses.