We shouldn't forget the history of SQL. I wasn't there, but my impression has been that it was originally written so that non-technical users (business decision

We shouldn't forget the history of SQL. I wasn't there, but my impression has been that it was originally written so that non-technical users (business decision makers) could write queries and have access to data in order to make business decisions. The data accessibility feature is ostensibly already built into the language. I think this original vision never ended up working out. I believe that business decision maker brains are not the same as SQL query writing brains. You need to be able to choose some facts, ignore the rest and persuade people. So this product adds (added) a middle layer in between the end user and the database. Either the user could learn this, or they could just learn SQL. But if the end users really care about what the data shows, they might as well just learn to write SQL queries, they aren't that hard. The reality is that end user business decision makers may not care that much about the SQL query output from data sets that may have a whole series of built in errors and biases anyways. I think business decision makers want to make decisions based on gut feel. In bigger companies and publicly traded companies, they then pay data analysts to produce data analyses that support those decisions, to CYA. In order to accomplish that, you don't need this tool, you just need vanilla SQL. The successful (LLM) tool would essentially have the business decision maker write a prompt that says: "I want to do X. Write me a report using this dataset that supports my decision". Yes?