co-author of blog post here.<p>We covered some of this, at a high level, here: <a href="https:&#x2F;&#x2F;blog.twitter.com&#x2F;2015&#x2F;the-what-and-why-of-product-experimentation-at-twitter-0" rel="nofollow">https:&#x2F;&#x2F;blog.twitter.com&#x2F;2015&#x2F;the-what-and-why-of-product-ex...</a><p>Certainly not everything needs to be A&#x2F;B tested -- depending on the nature of the change and the kind of insight one is looking to get, MAB may be better, if it applies, or a number of other approaches can be more beneficial, including not running an experiment at all. After all, Twitter itself came from a side project at the podcasting company Odeo. If Twitter was a&#x2F;b tested, I&#x27;m sure it wouldn&#x27;t move any podcasting metrics in a meaningful way :).<p>I&#x27;m obviously biased -- but I&#x27;ve seen really important insights gained from A&#x2F;B tests, and wouldn&#x27;t dismiss them too easily.