In a GAM, you are estimating the non-linear functions for all variables in the model simultaneously. Moreover, GAMs allows for smoothing techniques such as regression splines, which allows you to cast GAMs as a large penalized GLM. This has ties to Bayesian regression and mixed effects models.
In a GAM, you are not estimating a bunch of individual smoothers in isolation and then throwing them in a model.
