Elon Musk: preference

Transcript context

…Can you just speak to what it takes for a great engineering team for you? What I saw in Memphis, the supercomputer cluster, is just this intense drive towards simplifying the process, understanding the process, constantly improving it, constantly iterating it. Well, it’s easy to say ‘simplify,’ and it’s very difficult to do it. I have this very basic first principles algorithm that I run kind of as a mantra, which is to first question the requirements, make the requirements less dumb. The requirements are always dumb to some degree. So, you want to start off by reducing the number of requirements, and no matter how smart the person is who gave you those requirements, they’re still dumb to some degree. You have to start there, because, otherwise, you could get the perfect answer to the wrong question. So, try to make the question the least wrong possible. That’s what question the requirements means. And then, the second thing is try to delete whatever the step is, the part or the process step. It sounds very obvious, but people often forget to try deleting it entirely. And if you’re not forced to put back at least 10% of what you delete, you’re not deleting enough. Somewhat illogically, people often, most of the time, feel as though they’ve succeeded if they’ve not been forced to put things back in. But, actually, they haven’t because they’ve been overly conservative and have left things in there that shouldn’t be. And only the third thing is try to optimize it or simplify it. Again, these all sound, I think, very obvious when I say them, but the number of times I’ve made these mistakes is more than I care to remember. That’s why I have this mantra. So in fact, I’d say the most common mistake of smart engineers is to optimize a thing that should not exist. Right. So, like you say, you run through the algorithm and basically show up to a problem, show up to the supercomputer cluster, and see the process, and ask, “Can this be deleted?”…

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