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For all the reasons listed by the other commenters, this is not a great article about bluegrass or software development. There are some parallels, though. Bluegrass music was primarily a male-dominated genre, but that is changing. Early pioneers like Lynn Morris, Hazel Dickens, etc. opened the door, Rhonda Vincent and Alison Krauss pushed it open, and Molly Tuttle, Sierra Hull, and Sarah Jarosz have come through. There's little doubt in mainstream bluegrass now that women can be spectacular (Molly just won IBMA Guitar Player of the Year), though there are plenty of conservative pockets left and even prominent successful women still encounter sexist attitudes and behaviour. Another is the presence of a thriving indie subculture. There are thousands of small bands achieving modest regional amounts of success. Two examples from tech: Clive Thompson plays in the Brooklyn 80s covers band The Delorean Sisters http://www.deloreansisters.com/ and I play in the New Zealand progressive bluegrass band The Pipi Pickers http://pipipickers.com . There are plenty of side projects of software developers, small pet projects that will never be "the next Linux" but which achieve a modest following and serve the purpose of being intellectual stimulation for the developer. The jump from hobbyist to professional is a big one, though bluegrass lacks the paychecks in tech. "Get good at it, and you can make literally tens of dollars playing bluegrass." My favourite comparison though is the headspace of developers and musicians. Both struggle to explain their inner processes, both crave flow state, both need a lot of practice and competence to reach that stage. Part of me suspects that a 10x developer, if such a beast exists, is mostly a function of having absorbed the language/framework/os so deeply that they aren't constantly losing flow state by hitting StackOverflow. Similarly, to play in the pocket and improvise fluidly requires hours of practice and the internalising of the physical actions required to make a given sound. Anyone trying to figure out on the fly where a D note is, is not in that flow state. Neither seems at risk of being automated away. Deep Learning is making inroads into styles and genres (e.g., https://arxiv.org/abs/1801.00887) but little sounds like it could replace musicians and composers any time soon. And while deep learning systems are being used to tune deep learning systems, we're still far away from software being generated from problem descriptions or specifications. (Please throw links at me if I'm wrong!) |