I find it useful to frame performance of pure software in two fairly distinct categories: 1. Efficiency, which I define as minimising losses i.e not writing th

I find it useful to frame performance of pure software in two fairly distinct categories: 1. Efficiency, which I define as minimising losses i.e not writing things inefficiently, avoiding artificial complexity, bloat and keeping code simple. Performance hits here can also be a 1000 cuts problem when depending on many 3rd party pieces while having people chanting "premature optimisation" at you. 2. Optimization, which I define as employing specialist algorithms (which sometimes come in the form of entire tech stacks these days) with the cost of added complexity (and potentially performance trade) to get performance beyond the basic or naive yet efficiently implemented methods. The cost benefit ratio to these is not always worth it, especially in the beginning. Hopefully the point I'm trying to make should be obvious, that attempting #2 before #1 is a bad idea, and in less explicit words I suspect this is kind of what the author is getting at... Yet it's not all that uncommon to see someone trying to fit a turbocharger to a cheese skateboard with 64 triangular wheels.