This is a whole class of problem, it seems to me. A semi-automated approach can seem fine when there's an executive function over the top of it, exercised by someone who has not just the knowledge, but current and honed knowledge. But over time, what's keeping that knowledge current and honed?

The airline industry has talked about this, of course, and adoption of robotic surgery has opened up a whole new training problem, because its escape hatches when it goes wrong or can't complete a procedure is often "complete the surgery manually". Which is fine on Day 1 of robotic surgery, but what about day 2 when surgeons typically don't have hundreds of similar procedures under their belts? And where the only time they're called on to exercise the skill is in difficult edge cases?

We have basically turned driving a standard transmission into a weird old person quirk or niche enthusiant skill in the United States. If an automatic transmission required a similar manual fallback or check, how well would that work? Well, it would work fine if basically everyone already had a lot of practice driving a manual--but now? It wouldn't work well at all. Of course, automatic transmission don't fail like that, and are a lot better at switching gears than AI assistants are at generating code. I worry about the semi-automated approach to self-driving, where the driver may not actually have currency with their driving skill, and where--in the instance that it's necessary--a driver has to react to more complicated situations (they don't have practice with the simple ones, and they have to react not to a hazard but to their car's failure to react to a hazard).

>It “feels” like an older programmer seeing a younger web dev and going “you’re wasting MB of memory!”

I crammed a gigabyte of ASCII into a string in FreePascal, it was glorious!

Waste all the MB you want!

(I'm 59)

> And as also pointed out by others, it not only requires effort, but knowledge, and that knowledge will be systematically degraded the more AI-ish code generation is used.

How is that different than the plague of junior devs we've always had? Devs will get more senior by identifying and correcting issues in AI code rather than code from their peers. Seems OK, like we just got a whole lot more coding capacity.

Why do you worry that’s going to be a real problem?

It is. There are a lot of problems with copilot, but one magical thing is the way it rewards best practices like thinking through what a function is supposed to do before starting to write it.

If you write a good comment describing name, inputs, outputs, logic, and exceptions, the "generate code from comment" capability is kind of amazing. I'm a terrible, hacky programmer, and it has wholly converted me to documentation-first.

I think that can surely be the case, but just like any AI there may need to be manual review to asses what is the most optimal way to go about task X, and retrain.

I can see this go both ways:

boilerplate code being a great generic solution to a set of problems, but a more seasoned programmer may say “that works, but for our use case the trade offs don’t make sense”

Or alternatively, “this code wasn’t something I knew I could do in language X, and it’s far more efficient”