is not generic, it is highly specific. Microprocessors, IoT, database internals, web services, user experience, mobile apps, embedded systems, cryptography, animation, training models for generative AI, machine learning… Golang, python, COBOL, lisp, perl, React, brainfuck, ruby, rails, java, jruby, F#, C, C++, C#, javascript, typescript? What version, which frameworks, which libraries, what data models? What adjacent skills, market segments, or other subject matter expertise… design, security, compliance, data visualization, marketing, sales, pre-sales, post-sales, finance, banking…? What stage of maturity? What scale of usage? Shrinkwrapped software? The Mars Rover? Startup, scale-up, Fortune 500, international finance? 5 engineers, 5000 engineers, 50,000 engineers? Open source, closed source? Consulting? Remote, in-office, hybrid? ✨ ✨ ✨ First: how are you measuring productivity? I have a problem with the implication that there is One True Metric of productivity that you can standardize and sort people by. Consider, for a moment, the sheer combinatorial magnitude of skills and experiences at play: Also: people and their skills and abilities are not static. At one point, I was a pretty good DBRE (I even co-wrote the book on it). Maybe I was even a 10x DB engineer then, but certainly not now. I haven’t debugged a query plan in years. “10x engineer” makes it sound like 10x productivity is an immutable characteristic of a person. But someone who is a 10x engineer in a particular skill set is still going to have infinitely more areas where they are normal or average (or less). I know a lot of world class engineers, but I’ve never met anyone who is 10x better than everyone else across the board, in every situation. Secondly, and more importantly, So what?