Hmmm. Maybe. What I've found is that IT often re-invents past designs and methods to solve modern problems. Matter of fact, the way the cloud providers scaled was to re-implement mainframes on x86 boxes. The next level is applying lessons from older research in modern ways to improve efficiency of various parts of HW and SW. If anything, quite a few people came up with timeless lessons that teach you how to do efficient, reliable computation. They keep getting reused.

So, I don't think we can take it as far as author is suggesting where it's like classical vs quantum physics. Maybe at ASIC vs software level. Even those were partly joined with synthesis & coprocessing tools. I just don't see it as every high-level description I read about things is based on similar principles at each layer of the stack. Given similar constraints or goals, you would use similar strategy. There's certainly divergence or outliers but more repetition of patterns than anything.

The only myths are that technology/fads X, Y, and Z should've been widespread adopted over the ones (or enhancements of them) that consistently worked. The author is seeing results of people building on stuff that came with assumptions that don't match new problem. Or people straight-up ignoring root cause in their solutions or methods. Common problems.