The authors propose a generalization of the conjugate gradient method that uses multiple preconditioning, by combining them automatically in an optimal way. Their new algorithm obtains an energy norm minimization property, while maintaining \(A\)-conjugation and orthogonality properties similar to the preconditioned conjugate gradient method, but with iterates constructed in a generalized Krylov space incorporating an arbitrary set of preconditioners.