I found it was nearly impossible to enjoy because a single numerical distance metric provides almost no help in figuring out what direction to move to improve your guess, and any change in the distance metric when you're far away from the solution is really just a false signal - i.e. "mother" gives a score of 20, "grandmother" gives a score of "23", but grandmother isn't actually closer to the final word ("malfeasance") in any meaningful way than mother is.
Another issue with it is that the training set comes largely from newspaper articles, which means the semantics it learns sometimes have significant artifacts resulting from associations that are common in news coverage but not the English language in general.
As a result my own experience with it was "think of random guesses endlessly until you end up somewhat close and then be frustrated at what you learn about the embedding when you eventually converge on the answer."