Your points are good. I did not intend to suggest that software developers should make the kind of decisions that lead to "mangled and indecipherable set of 'cr

Your points are good. I did not intend to suggest that software developers should make the kind of decisions that lead to "mangled and indecipherable set of 'critical sections'". More that developers who understand their tools at a lower level are likely to choose architectures with better computational efficiency. Simple things like acyclic ownership, cache locality, knowing when to use value vs. reference semantics, treating aggregate data as aggregate instead of independent scalars, etc. Often these choices do not present a serious dichotomy between readability and performance. You just need to make the right choice. Developers who understand their tools better are more likely to make the right choice. My main argument is that this kind of background knowledge should be more widely taught. Performance is often presented as a tradeoff where you must sacrifice readability/modifiability to get it. I think this is not true. Choosing good data structures and program structure is not mutually exclusive with having "a very extensible and malleable implementation".