I feel like there is something really synergistic between SQL and what an LLM is capable of. I've run some experiments where I simply feedback the last sql err

I feel like there is something really synergistic between SQL and what an LLM is capable of. I've run some experiments where I simply feedback the last sql error/result set+prior query+goal and I've had iterations reach success, in one case after hitting the wall 12 times. OpenAI's models will dive straight into schema definition and system tables if you are clever in your prompting. Many RDBMS implementations support this. Table names, column names, indexes, foreign keys, and matching descriptions for all in the most ideal case. The fact that you can call OAI inference APIs directly from a SQL Server sp makes a little bit nervous about the whole skynet thing.