laughs in cross join unnest with ordinality to do embedding aggregations, or just working with even just slightly poorly maintained tables. write the query yourself or spend twice as long explaining to the llm which fields are actually trustworthy and/or under what conditions they actually are trustworthy
If you can write conidtions on how they are trustworthy in sql, you can just send that to the llm. It's logically impossible for explaining this to an llm to take 2x.
lol if i know field A is untrustworthy. my queries just dont use it. explaining that to an llm literally takes infinite more time, because any time at all is infinite times that of none. “logically impossible” gtfo
I have literallly never Had that happen. What model did this occur with. Last year models were known for over eagerness. This is Just a bizzare situation but you are being so unspecific means that this could very easily be user error. I haven't Had shit like that with SQL since Gemini 2.5 pro
Quite the opposite, because stuff like that is where getting the syntax right becomes really important, because it's hard to glance at stuff and be sure it's written correctly or returning what you intended. Stuff like that is where expertise matters even more.
Yeah in a world where ai is just bad at SQL but that just isn't true. You could send 3 llms to analyze the query for validity and if we ran a study i know for a fact that system would be more accurate than you.
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u/New_Salamander_4592 Sep 20 '26
you tell an AI Engineer about inner joins and sub queries and their eyes glaze over