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If our starting point is that programming is mostly about skills, productivity starts getting interesting - what does productivity mean? My personal take is th
by itamarst 9y ago
If our starting point is that programming is mostly about skills, productivity starts getting interesting - what does productivity mean?
My personal take is that it means solving problems with less wasted effort. Less code (a 0.1× programmer can solve problem with 10% of the code - https://codewithoutrules.com/2016/08/25/the-01x-programmer/ https://codewithoutrules.com/2016/08/25/the-01x-programmer/), but also by solving the right problem, and coming up with better solutions (https://codewithoutrules.com/2017/10/04/technical-skills-productive/ https://codewithoutrules.com/2017/10/04/technical-skills-pro...).
These are all skills you can learn. And I think focusing on learning technologies obscures a lot of these skills, since they're about communication and listening and project management.
For productivity in terms of technological knowledge I'm starting to think that, since choosing which tool is more important than how to use it, a better way to get better is to study case studies. Instead of trying to learn "how can I use Mongo, how can I use PostgreSQL" you try to learn "when should I use Mongo, when should I use PostgreSQL".
I'd love to hear about good sources of case studies. http://www.aosabook.org/en/index.html http://www.aosabook.org/en/index.html is good, but doesn't cover kind of programming one would do at a company, much.
- iamcasen 9y agoThis is exactly correct. In the past, I didn't consider myself an excellent programmer, because I struggled to solve esoteric number permutation problems and recursive graph search problems during whiteboard interviews. It seemed to me that all my peers could do it, and they were getting good jobs for it. Over time I learned that the real value comes from solving the right problems, and recognizing wasted effort. It comes from architecting systems that are easily maintainable. That's what makes money in the business. Solving narrow, intensely interesting algorithms, is a rare case that is not widely needed in the industry at large.