This still seems too simplistic. You say you can't know whether it's right unless you know the topic, but that's not a binary condition. I don't think anyone "knows" a complex topic to its absolute limits. That would mean they had learned everything about it that could be learned, and there would be no possibility of there being anything else in the universe for them to learn about it.

An LLM can help fill in gaps, and you can use what you already know as well as credible resources (e g., textbooks) to vet its answer, just as you would use the same knowledge to vet your own theories. You can verify its work the same way you'd verify your own. The value is that it may add information or some part of a solution that you wouldn't have. The risk is that it misunderstands something, but that risk exists for your own theories as well.

This approach requires skepticism. The risk would be that the person using it isn't sufficiently skeptical, which is the same problem as relying too much on their own opinions or those of another person.

For example, someone studying statistics for the first time would want to vet any non-trivial answer against the textbook or the professor rather than assuming the answer is correct. Answer comes from themself, the student in the next row, or an LLM, doesn't matter.