- retired programmer, student of Computer Science, 40 years experience

Personally, I stay away from ai-gen code because I don't want to debug someone else's code when I could just write my own. AI-gen solutions, from my experience, only fall into a handful of categories:

1. boiler-plating

imo, this should be done by bespoke tools, which are crafted by someone who understands the domain - and that's how it's been done for ages. If you can get accurate boiler-plating from ai-gen and there's no tooling to help - go for it, but you'll miss out on understanding what that boiler-plating does if you don't already know

2. trivial solutions

IE, solutions that are obvious, like "write me a function which determines if a number is even". Sure, this prompt came from someone who doesn't understand their own language and tooling, so it's already coming from a low bar. But the solution here is an obvious one, doesn't require a generated function, is literally built into the language

3. completely wrong solutions

The amount of time I've wasted reading ai synopses when googling a technical issue... Egad. Because they've all been a waste. I spent 1/2 an hour with chatgpt trying to resolve an issue with webpack, and despite me telling it several times that it was in webpack 4, it kept trying to offer incompatible solutions that work in webpack 5. This is just one example, but the number of times I've seen ai outputs and just gone "wtf, no", is not insignificant. These may sometimes be not as harmful as the next case, because sometimes even people with low skill in the area can spot the problems, or they simply don't compile, ie break before they have a chance to manifest havoc.

4. subtly-wrong solutions

This was my experience when being presented to by people saying "look what this model does". The problem is that others in the room didn't spot the bugs until I pointed them out, so I'm not sure if that's due to overconfidence in the output or they just have a skill issue. Subtly-wrong solutions without someone to correct them are the worst because they will appear to work most of the time and present weird bugs sporadically. One output I saw was around doing something based on the day of the week, and the output just skipped sundays, for no good reason (was counter to the requirements)

None of these outcomes are useful to me, and they eclipse, by far (in my experience), the maybe 1% of useful outputs. My conclusion is that it's more time-efficient to do the work myself, because I understand the long tail of debugging and extension and all the things the ai subtly cocks up.

Some are curious, some are anxious about getting things wrong, some are doing the bare minimum and ya some are full of themselves. Each one exploits the tool differently. But I get them to ask it about these things too (are there things I am missing cause I want to get this right/why is my boss saying I am full of myself/my boss told me he doesn't have time to teach me about X but if I am curious thats something I should look into etc) which you couldn't do with them in the past.