I thought the point of “clean code” was to make a software source code base comprehensible and maintainable by the people who are in charge of working with and deploying the code. When you optimize for people reading the code rather than some kind of performance metrics, I would expect performance improvements when you switch to performance optimization. The trade-off here is now code that’s more performant, but that’s more difficult to read, with interdependence and convolution between use cases. It’s harder to update, which means it’s slower and more costly (in engineering resources) to upgrade.

In a lot of modern software, you don’t need extreme performance. In the fields that do, you’ll find guidelines and other resources that explain what paradigms to avoid and what are outright forbidden. For example, I have heard of C++ exceptions and object-oriented features being forbidden in aircraft control software, for many of the reasons outlined in this article. But not everyone writes aircraft control code, so rather than saying clean code is “good” or clean code is “bad,” like a lot of things this should be “it depends on your needs.”