Often the problem best solved by AI isn't "How do I use Anisble to do X" But simply knowing that you should be using Ansible at all. Or which features to use. Then you can be laser-focused on learning exactly the right part of Ansible.
It also helps you to move away from familiar but hacky solutions towards much more standard and robust ones - the AI doesn't approach the problem with your many years of battle scars and baggage but instead sees your problem space with fresh eyes and recent data.
But why use AI for that in the first place? You can just, uh, google things. Like "software that does X". You would get a better result from forums and blogs and such. When doing research, AI really feels like an unnecessary middleman when you know how to do research on the internet. Which I would argue is a basic skill in the modern world.
So your point went from: they shouldn’t have done what they did because it likely took much longer than necessary by using AI - to: they shouldn’t have done what they did because they didn’t take long enough learning it without AI to do it. I think you moved the goalpost to the opposite side of the field.
In this thread you chastised them for “using it in production” when their use case was simply a lab for teaching. And you suggest that googling for days and reading countless blog posts and forums is impervious to wrong or dated information, which is quite a position to take.
Their use case was a perfect fit for a LLM, and I suspect it saved them weeks of effort in the process, with likely fewer security flaws as a result. But keep up that anti-LLM advocacy, I’m sure you are very close to achieving the goal of society abandoning the technology.
Keyword based search (Google) requires the user to know which keywords to enter. It's very bad at finding things related but with different words to what the user is trying to search. Sometimes half the challenge is figuring out what the experts call the task you are trying to achieve.
Set up some desktops with code -> Declarative configuration management -> Ansible
This task seems easy to an expert. As someone who's been a professional learner (as a programmer) for 25 years, it's far far easier with ChatGPT to get a summary of a field and a starting point than it ever was with just Google and some random blogs bouncing around the internet. Now with modern o3 (Chat GPT Pro) models you can go from a vague question to a summary of suitable solutions and some code samples in one prompt.
Now obviously AI is not able to create complete solutions alone. It's just another tool. Sometimes ChatGPT makes glaring mistakes in how it approaches a problem. So (for now) it is still a collaboration requiring smart humans in the loop.
It also helps you to move away from familiar but hacky solutions towards much more standard and robust ones - the AI doesn't approach the problem with your many years of battle scars and baggage but instead sees your problem space with fresh eyes and recent data.