We give a concise introduction to the theory of causal transport and to (filtered) stochastic processes endowed with the adapted Wasserstein distance. In particular, we review recent advances in understanding the geometric structure of the space of stochastic processes. We then explore applications in nonlinear optimal transport, mathematical finance, and geometric inequalities. Finally, we outline several open problems and possible directions for future research.