> The problem with using AI to review AI is that what you're checking is the same as what you're checking it with.

This isn't true. Every instantiation of the LLM is different. Oversimplifying a little, but hallucination emerges when low-probability next words are selected. True explanations, on the other hand, act as attractors in state-space. Once stumbled upon, they are consistently preserved.

So run a bunch of LLM instances in parallel with the same prompt. The built-in randomness & temperature settings will ensure you get many different answers, some quite crazy. Evaluate them in new LLM instances with fresh context. In just 1-2 iterations you will hone in on state-space attractors, which are chains of reasoning well supported by the training set.