This was perhaps a very hard problem for an LLM, as the Packer tool’s nature is to manage layers of context. Environment variables passed through templates then passed to scripts which themselves might be in other frameworks. So in this case it to be confused about what was Ansible syntax and what was Packer.
So the bot seems to have different failure modes than humans. Distinguishing context layers seems to be a weak point. And an answer that is a wild guess looks as authoritative as a solid answer. But it’s still extremely impressive.
I started trying to learn Clojure with this years advent of code, but got stuck and first tried to use ChatGPT to solve it. My impression matches yours in that it consistently produced non working code and even when told about the error it was unable to fix it.
Then I instead decided to let it use any tool or language it knows, and I'm now documenting how it's doing solving the things.
If you're interested, here is Day1 where I first tried to use it to help me solve it with clojure, but then I gave up and asked for any concise solution. So I got a working solution with `awk` https://blog.nyman.re/2022/12/02/chatgpt-does-advent.html
The second day I just let it pick anything, and it successfully solved the day2 puzzle using python which seems to be it's go-to language. https://blog.nyman.re/2022/12/03/chatgpt-does-advent.html
Not so weird: this judgment could apply to a lot of humans and to whole fields of human activities, if not to the essence of life itself.
In particular it reminds me of a con man every expert could see through, but that mesmerized management with his buzzwords talk, causing an exodus of competent people and high turnover for a few years, and most likely many millions in damage.
With advanced enough AIs handling full remote jobs, this could be done on steroids, getting you a lot of income while wreaking havoc in the companies.