I think this is premature optimisation. LLMs are the general tool here - in principle we should try first to adjust LLMs to search instead of doing it the other way around.

But really I think that LLMs should use search as just one of their tools - just like humans do. I would call it Tool Augmented Generation. And also be able to reason through many hops. A good system answer the question _What is the 10th Fibonacci number?_ by looking up the definition in wikipedia, writing code for computing the sequence, testing and debugging it and executing it to compute the 10th number.