But now it's so easy with GPT to get the queries exactly as my use-case needs them. And it's not just SQL queries, it's anything data querying related, like Google Sheets, Excel formulas or otherwise. There are so many niche use-cases there which it can handle so well.
And I use different SQL implementations like Postgres and MySQL and it's even able to decipher so well between the nuances of those. I could never reproduce productivity like that. Because there's many nuances between MySQL and Postgres in certain cases.
So I have quite good trust for it to understand SQL, and I can immediately verify that the SQL query works as I expect it to work, and I can intuitively also understand if it's wrong or not. But I actually haven't seen it be really wrong in terms of SQL, it's always been me putting in a bad prompt.
Previously when I had a more complicated query I used to remember a typical experience where
1. I tried to Google some examples others have done.
2. Found some answers/solutions, but they just had one bit missing what I needed, or some bit was a bit different and I couldn't extrapolate for my case.
3. I ended up doing many bad queries, bad logic, bad performing logic because I couldn't figure out a way how to solve it with SQL. I ended up making more queries and using more code.
I mean, I could consult my Tarot cards for insight on how to proceed with debugging the problem, that would not be useless. Same for Oblique Strategies. But in this case, I already know how to debug the problem, which is to change the logging settings on the ORM.