The user might say - I need a refund. The bot needs to know contextual information - order details, delivery tracking details etc.
Now you have written a prompt template that needs to be rendered with contextual information. This rendered prompt is what the model will use to decide whether to issue a refund or not.
Before you deploy this prompt to prod, you want to evaluate its performance - instances where it correctly decided to issue or decline a refund.
To evaluate, you can “replay” historical refund requests. The issue is that the information in the context changes with time. You want to instead simulate the value of the context at a historical point in time - or time-travel.