Of course, measuring response time vs. popularity is up to interpretation: it could be that as adoption increaess, people ask easier questions. However, I suspect the chart is actually undercounting the adoption benefit: the more questions are answered, the more people don't need to wait for answers because they can just search for old ones! As one measure, we see that a language's popularity relates to its answer corpus size:
Open source library repos are another case of a feature that improves with adoption: the library of builtins is ever expanding. Likewise, one of my favorite research projects is cooperative bug isolation, which exploits the adoption of a program to help narrow down causes of bugs. (AFAICT, most software companies do some form of tracking error and performance dumps.) A/B testing for feature design is also increasingly common. As another example, in academia, code completion tools are also increasingly incorporating corpus-based solutions. A corpus can provide more value than type and namespace based solutions because, for example, synthesized code completions will resemble what people would actually write.
I started sketching out the notion of adoption-oriented language design in a position paper last week. I struggled to think of features that couldn't be designed to strengthen with adoption. For example, verification, testing, security, program synthesis, and optimization could all be designed to automatically exploit adoption of either the language, the library, or a program. What strikes me is how little adoption is exploited today. Outside of the cases, am I missing any that are commonly practiced, or should be?