We propose an iterative algorithm taking as input a random matrix-valued linear operator, and characterize its behavior in terms of a limiting correlated Gaussian/semicircular process in a free probability space. We apply this iteration to a random version of the matrix discrepancy problem where given independent GOE matrices, one is asked to find signings so that the signed sum has as small of an operator norm as possible.