In my experience, they mostly just catch bugs. Stuff like "hmm, our much better looking signup flow underperforms... oh, the form is broken on Safari." That kind of thing.
This can be the case for A/B testing. Sure, you can increase ad clicks by 30% ... if you trick the user into clicking it through a carefully timed layout jump.
I think GP's argumentation may go in this direction. I'd probably not say A/B testing is the problem itself, it is a tool after all, but I could imagine it's sometimes not used very well.
Another point: Spotify's core flow changes so much (feels like almost daily) that I've lost all confidence in using it.
a double blind test can help you determine the most effective way to cause pain to a monkey, but it will never answer the question of whether you should be doing so.
"Network Experimentation at Scale" from Facebook describes how difficult this problem is. Most A/B test frameworks don't reach this level of sophistication. It does make some sense to just ship things if you don't have time to build out something like that. (disclosure: I worked at Twitter long ago)