Claiming that gradient descent is a great algorithm certainly wasn't the goal of this article. But GD is the basis from which most other iterative algorithms stem, and it's worthwhile having a good understanding of its inner workings as a prerequisite for more advanced algorithms.
Personally I found http://sebastianruder.com/optimizing-gradient-descent/ interesting - it goes into the advanced variants like nesterov, adadelta, etc