The ability of AI to write things with lots of boilerplate like Kubernetes manifests is astounding. It gets me 90-95% of the way there and saves me about 50% of my development time. I still have to understand the result before deployment because I’m not going to blindly deploy something that AI wrote and it rarely works without modifications, but it definitely cuts my development time significantly.
100% this. I generally use AI to help with edge cases in software or languages that I already know well or for situations where I really don’t care to learn the material because I’m never going to touch it again. In my case, for python or golang, I’ll use AI to get me started in the right direction on a problem, then go read the docs to develop my solution. For some weird ugly regex that I just need to fix and never touch again I just ask AI, test the answer it gices, then play with it until it works because I’m never going to remember how to properly use a negative look-behind in regex when I need it again in five years.
I do think AI could be used to help the learning process, too, if used correctly. That said, it requires the student to be proactive in asking the AI questions about why something works or doesn’t, then going to read additional information on the topic.
Do you want the entire article in the headline or something? Go read the article and the journal article that it cites. They expand upon all of those terms.
Also, I’m genuinely curious, what do you mean when you say that there is “No such thing AS “AI””?