Recently, the time-to-equilibrium (mixing time) of many examples of Markov chains in random environments have been analyzed using a common ansatz: when an auxiliary process achieves the correct entropy, the original process is near stationarity. I will review this approach in several examples, and mention some recent work in the non reversible context. This talk will aim to be broadly accessible.