It is a fantasy for a lot of entrepreneurs, scientists and engineers to develop a software project that can automatically perform feature generation, training, and prediction automatically.
Of course it is a wishful thinking. There is no free lunch.
In big companies that have abundant resources (training data, brains, clusters), they can probably so something like deep learning to get the relevant features, and build classification models. It is almost automatic. It virtually takes no manual addition of human knowledge. Some scientists and engineers are enjoying the strength of word2vec, but it takes a lot of computer resources to even train a word2vec model.
If we do not have enough training data or computing resources, to get a good classifier, we ought to add human knowledge to generate features. We might even need to impose some rules to convert the raw data to sensible features. The rules might be regular expressions, or some calculations, or some filters, or it involves a knowledge database (like WordNet). Things might be simplified if the problem we are dealing with is in a specific domain, that reduces the amount of human knowledge we need to add.