In this case, you just want your feature store to have a timestamp column as a timestamp key. You would compute your features as of whatever dates you like and add them as features, and those are used to train. At runtime, to make a prediction as of "now", you pass the current time as the value of the timestamp key. Under the hood it's an as-of join, which matches the latest time <= your value when finding the matching row.