We analyse in a systematic way the occurrences of a remarkable structure in the theory of integrable probability that we call a ``max-independence structure'', when random variables are constructed as a maximum of a sequence of independent random variables. The list of treated examples contains~: the $ GU\!E $ and $ GO\!E $ Tracy-Widom distributions, the extreme eigenvalues/eigenangles of random hermitian/unitary matrices (and in particular the historical example of the $ GU\!E $ extreme eigenvalues), the Hopf-Cole solution to the $ KPZ $ equation with Dirac initial condition (continuum random polymer) and the symmetric Schur measure. % In this last case, the largest part of the underlying random partition is the maximum of an i.i.d randomisation of the deterministic sequence of negative integers. In the case of the $ GU\!E $ Tracy-Widom distribution, the laws of the random variables use a rescaling of the prolate hyperspheroidal wave functions that were introduced by Heurtley and Slepian in the context of circular optical mirrors, and in the case of the $ GU\!E $, the distributions use the sigma-form of the Painlevé $ I\!V $ equation. To illustrate the utility of such a structure, we rescale the largest eigenvalue of the $ GU\!E $ written as a maximum of $N$ independent random variables with the classical Poisson approximation for sums of indicators. We use for this the Okamoto-Noumi-Yamada theory of the sigma-form of the Painlevé equation applied to random matrix theory by Forrester-Witte. By doing so, we find a new expression for the cumulative distribution function of the $ GU\!E $ Tracy-Widom distribution which is shown to be equivalent to the classical one using manipulations à la Forrester-Witte.