This is a nice insight. I slightly disagree with the first example in a gambling context, although it makes sense in the context of information theory. I don’t think the choice of prior is right when giving 20:1 posterior odds you’d be willing to bet on. A better prior should be related to the probability of a random person lying about their name when introducing themselves. And the posterior then doesn’t really depend a lot on what name he says.