Eigenvalue algorithms such as QR are completely integrable systems. Random matrix theory is integrable in the sense that key statistics are described by Painleve functions, which are themselves solutions of integrable Hamiltonian systems. What happens if we combine these two integrabilities and consider the computation of the eigenvalues of a random matrix? More generally, what about other standard numerical algorithms applied to random data?