Many Physics problems are formulated as the minimization of a functional. Therefore, methods for solving these problems require differentiating maps whose input and/or output are functions—commonly referred to as variational differentiation. This procedure is difficult to perform manually and is poorly addressed by existing symbolic and algorithmic differentiation systems. In this talk, I will discuss what makes the variational differentiation challenging to automate. Then I will suggest a pair of combinators as the silver bullet and showcase their power on a few non-trivial problems.