This test plainly shows that even with the real solution in the training data, the wrong answer is written as though it's the correct answer. A human would say, "I'm not sure, I want to test it." The current AI summer is heaving with breathless claims of intelligence, comprehension, reasoning, etc.
I think these claims need to be balanced with a cold shower of reality. Personally, I find LLMs very impressive at what they do well; generating and summarizing and translating. People apologizing for LLMs' performance at straight-forward reasoning and programming tasks, suggesting various crutches and head-starts, gives me the creeps. It's not the Messiah. It's a very naughty computer program.
We're replacing React with Htmx at work (about a year into it) and have found WebComponents to be very useful to re-use some of the React components that we want to preserve and treat a bit like using native browser widgets (input, select, textarea). Specifically, a WebComponent lets you hook into the lifecycle of a DOM element that is being modified by the outside world (morphdom via Htmx). In the event of attributes changing, you want to tell the React component about that. And in the event of the node being removed from the DOM, you want to tell React to run its cleanup procedures. I think that we weren't able to do this in a clean, efficient way without WebComponents.
The end result is that we can stick to Htmx's way of doing things, i.e. keeping all business logic state on the server, and only a few conservative things are client-side (such as currently focused element, text being typed in an input, things like that). Every step we take towards this, it offers a much better user experience with fewer bugs and race conditions, so it's worth the effort.