To be clear, the specific paradigm we're referring to is this way of writing transforms as functions where the parameter name is the upstream dependency -- not the notion of delayed execution.
I think there are two different concepts here though:
1. How the transforms are executed
2. How the transforms are organized
Hamilton cares about (2) and delegates to Polars/pandas for (1). The problem we're trying to solve is the code getting messy and transforms being poorly documented/hard to own -- Hamilton isn't going to solve the problem of optimizing compute as tooling like polars, pandas, and pyspark can handle that quite well.