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I'm very curious what these development workflows are where writing "boilerplate" code is so common, especially that AI-generated is good enough. It's very rare for me to need this, and Ileven then I generally have spent more time cleaning up wjatbit built than the time it saved me.
It could be level. Less experienced engineers find the boilerplate spit out by copilot extremely useful, more experienced find it more in the way.
Is some of this just caused by more experienced folks being less inclined to learn AI tools? Maybe. I think experience writing code is the bigger factor though.
I'm trying real hard to find it useful. I can see it eventually being more useful, but it's just not worth the cost.
Maybe, it's just really rare for me to be looking at a "blank page'. 95% is an incremental improvement on top of something existing. So "boilerplate" would come into my workflow pretty rarely.
Maybe some frequently-changing data science or data mining tasks?
By saying "boilerplate", I mean constructors, simple methods and even small classes that have some "standard" implementation. Copilot easily writes simple constructors, class initialization and destruction. It can suggest small method implementation, right after I added its declaration to related interface. Anything, that can be done almost without thinking of how to do it because there are standard practices, is handled by Copilot. It's not perfect, it can write a whole method at a time, or only line by line, or refuse to suggest any code. But it often writes valid code.