If an LLM can solve a riddle of arbitrary complexity that is not similar to an already-solved riddle, have the LLM solve the riddle "how can this trained machine-learning model be adjusted to improve its riddle-solving abilities without regressing in any other meaningful capability".

It's apparent that particular riddle is not presently solved successfully by LLMs, as if it were solved, humans would be having LLMs improve themselves in the wild.

So, constructively, there exists at least one riddle that doesn't have a pattern similar to existing ones, where that riddle is unsolvable by any existing LLM.

If you present a SINGLE riddle an LLM can solve, people will reply that particular riddle isn't good enough. In order to succeed they need to solve all the riddles, including the one I presented above.