Part of the answer is probably that DL is not a single algorithm or a class of algorithms, but rather a framework or a paradigm for building such algorithms.

Sure, you can take a SOTA model for ImageNet and apply it to similar image classification problems, by tuning some hyperparameters and maybe replacing certain layers. However, if you want to apply it to a completely different task, you need to build a different neural network.