I like the idea of SQL as the "common tongue" because provided the query is reasonably terse it's easy for the human to verify and reason about, there's shitloads of it in the LLM's training set, and (usually) the database doesn't lie. So you've mitigated some major LLM drawbacks that way.

Another thing SQL has in it's favor is the ability with tools like trino or datafusion to basically turn "everything" into a table.

EDIT: thinking on it some more, though, at what point do you just know off the top of your head the small handful of SQL queries you regularly use and just skip the expensive LLM step altogether? Like... that's the thing that underwhelms me about all the "natural language query" excitement. We already have a very good, natural language for queries: SQL.

> small handful of SQL queries you regularly use

Give those queries to the LLM and enjoy your sleep while the agent works.