As a senior developer, I don’t find copilot particularly useful. Maybe it would have been more useful earlier in my career, but at this point writing a prompt to get copilot to regurgitate useful code and massaging the resulting output almost always takes as much or more time as it would for me just to write whatever it is I need to write. If I am able to give copilot a sufficiently specific prompt that it can ‘solve’ my problem for me, I already know how to solve the problem and how to write the code. So all I’m doing is using copilot as a ghost writer instead of writing it myself. And it doesn’t seem to be any faster. The autocomplete features are net helpful because they’re actually what I want often enough to offset the cost of reading the suggestion and deciding if it’s useful. But it’s not a huge difference (vs writing it myself) so that by itself is not sufficiently useful to justify paying the cost myself nor sufficient motivation to go to the effort of convincing my employer to pay for it.
Nah, it’s all hyped up bullshit that has to be babysat and manipulated to a degree that you may as well just write your damn code.
But beyond that, I’d argue that it’s actually damaging for engineering organizations, because it means the org is incurring the maintenance cost of code not written by its engineers and that has no real thought put behind it. Maybe you can eventually coax it to produce code that’s not completely broken shit, but it’s code that your org doesn’t actually “own” from a maintenance and knowledge-base perspective. The social aspect of code maintenance with this shit is always massively overlooked.
I have not and will not ever use AI generated code that I don’t thoroughly understand. If you properly understand the code you’re committing there shouldn’t be any damage. And beyond AI you should never commit code that you don’t properly understand unless it’s a throw away project.