It makes sense when users ask for information not available in the tokenized values though. In the abstract, a tool that changes tokenization for certain context contents when a prompt references said contents is probably necessary to solve this issue (if you consider it worth solving).
It's a fools errand. The kinds of problems you end up coding for are the ones that are blatantly obvious and ultimately useless except as a gotcha to the AI engines. All you're doing is papering over the deficiency of the model without actually solving a problem.
This is less a deficiency of the model, and more of a deficiency of the encoder IMO. You can consider the encoder part of the model, but I think the semantics of our conversation require differentiating between the two.
