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GitHub Copilot became my daily helper at work. While I'm not 100% satisfied with its code quality, I must admit it's very handy at writing boilerplate code. A few days ago, I had to write code without having internet access, and it was so disappointing to write boilerplate code by hand. It's an easy task, but it's time-consuming and unpleasant.
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?