> PAW reframes the foundation model from a per-input problem solver into a tool builder: invoked once per function definition, it produces a small reusable artifact whose subsequent calls per function application are cheap and offline.

Umm you can just get the LLM to spit out real functions instead of fuzzy functions and just run those real functions through real interpreters, which is also "cheap" and "offline".

> Each is the kind of fuzzy task that resists symbolic implementation but does not need an API call to a 30B-parameter model on every input.