[PheonixPharts]

> but no-one in the comments here is even mentioning it

The post has an entire section discussing this.

The problem with text-to-sql is that, as the post elaborates, writing SQL is not the problem. It's understanding the context and the data:

> On the other hand, a technical person would notice that the question doesn't make sense, and they would ask for more context. They would ask for details about the business person's hypothesis and the problem at hand. Then, they would explain what type of data is available, and work with the business person to formulate a precise and useful question.

Text-to-sql in practice is a solution that nobody was asking for, despite the insane number of SV startups shipping GPT-text-to-sql wrappers as products.

There certainly is like places where LLMs can help (post touches on this briefly), and that is in semantically exploring databases/tables/etc and contexts around data, but this is a very different project and would require a lot of curation from data teams to make it happen.