For example, a Bayesian expected utility maximizer programmed with a TM-based universal prior would not be able to realize that the prior is wrong.

What does it mean to "realize that a prior is wrong"? The mechanics of belief change in a Bayesian agent are fixed by the prior itself.

Nor would it be able to see that Bayesian updating is the wrong thing to do in some situations.

Bayesian updating is always the right thing to do. The only question is how to approximate a proper Bayesian update using efficient data structures and algorithms.

. . . it may be that there is a bunch of low-hanging fruit hiding just around the corner.

I would stay in the fruit tree metaphor and say they might be "hanging right over our heads".