> select price from rent_prices where city=”Los Angeles” AND month=”05” AND year=”2023” I have to say the best implementations out there are already far ahead.

> select price from rent_prices where city=”Los Angeles” AND month=”05” AND year=”2023” I have to say the best implementations out there are already far ahead. Naturally there are some context limitations with large database schema but those can be handled: - having an easy way to include/exclude tables ad hoc - importing database schema in multiple different data sources that you can switch between depending on usage And of course if AI isn't using the correct tables or columns, simple prime the prompt using autosuggest feature containing the tables and columns. Generating JOINS isn't really a hurdle if you have a good prompt template: - https://aihelperbot.com/snippets/cllovmlat000kmj0fedssj8c5 https://aihelperbot.com/snippets/cllovmlat000kmj0fedssj8c5 (notice it even uses the correct "film" tables even-thought it was instructed to find "movies" and naturaly category and category bridges table) - https://aihelperbot.com/snippets/cllnztzky0002mj0fa78hw0o2 https://aihelperbot.com/snippets/cllnztzky0002mj0fa78hw0o2 (it can also find lat/lng for Boston for AWS Athena, was demonstrating this for a Boston company) - https://aihelperbot.com/snippets/cllo1vwl6000wlb0fj5669zt4 https://aihelperbot.com/snippets/cllo1vwl6000wlb0fj5669zt4 (It can generate in Mandarin as well, but less capable than English. Same goes for German, French, Spanish and so) You can also have AI generate advanced SWOT analysis based on your database schema: https://i.imgur.com/JTv4QmX.png https://i.imgur.com/JTv4QmX.png