That's fair, but the subtitle was intended to be a little controversial. I could have included more datasets, but ultimately that just clutters the exposition -- instead I chose a dataset that can illustrate several different ways clustering algorithms can break. Ultimately it is meant to be a teaser as to why you should use HDBSCAN; the real answer is to grab the code and run it on your data, or your favorite test datasets, and see how it performs for you (because there is no substitute for that). I'm actually pretty confident you'll find the results impressive enough to make HDBSCAN a go-to choice for clustering.