Does anyone has examples where promoting and double checking is faster than doing it on your own?
I find it is faster in lots of cases where the solution is 'simple' but long and and a bit fiddly. As a concrete example from earlier today, I needed a function that took a polygon and returned a list of its internal angles. Can I write it myself, sure. Did copilot generate the code (and unit tests) for me in a fraction of the time it would have taken me to do it, absolutely.
Sorry I'm not in your domain at all, but shouldn't that be a library function? Properties of polygons seem pretty universal to me. Will AI replace carefully curated libraries with repeated boilerplate? Thus reducing reusabilty of human efforts?
It's a balance. Sometimes it's better to just to write a 10 line function and get on with your work, rather than dragging in a huge extra dependency to your project.
If there is a good library for it within the domain, ideally at some point the AI will suggest it. Can't wait until the AI writes it own library it will reference in future answers.
I find it is faster in lots of cases where the solution is 'simple' but long and and a bit fiddly. As a concrete example from earlier today, I needed a function that took a polygon and returned a list of its internal angles. Can I write it myself, sure. Did copilot generate the code (and unit tests) for me in a fraction of the time it would have taken me to do it, absolutely.