Huge scale typically leads to the opposite: more backend generalization, not catering to a specific front-end. That's why Facebook built GraphQL — because they run on anything, like fridges, TVs. That's specifically an attempt to avoid tailoring a backend to a frontend. The article argues that at small scale you shouldn't try to build a generalized backend for any imagined frontend. It's exactly how you would get unnecessary performance and complexity bottlenecks, when you really just need to serve your data the 1 or 2 ways that your front demands.

Yeah, our org has a big problem with over-generalization in our internal services that I've been pushing back on. Due to the large size of our org, they're under the false impression that our services are large-scale, but they're actually very small compared to anything external-facing.

When a partner team filed a feature request on our team, and I gave them an API that just does exactly what they need, they were like "that's it? No 1GiB graph response to DFS through?"