Having written more SQL than any other programming language by now, every time I've tried to use AI to write the query for me, I'd spend way more time getting the output right than if I'd just written it myself.
As a quick aside there's one thing I wish SQL had that would make writing queries so much faster. At work we're using a DSL that has one operator that automatically generates joins from foreign key columns, just like
credit.CLIENT->NAME
And you got clients table automatically joined into the query. Having to write ten to twenty joins for every query is by far the worst thing, everything else about writing SQL is not that bad.
(Shameless plug) writing the same joins over and over (and refactoring when you update stuff) was one of my biggest boilerplate annoyances with SQL - I’ve tried to fix that while still keeping the rest of SQL in https://trilogydata.dev/
yeah we’re doing something similar under the hood at AstroBee. it’s way way way easier to handle joins this way.
imo any hope of really leveraging llms in this context needs this + human review on additions to a shared ontology/semantic layer so most of the nuanced stuff is expressed simply and reviewed by engineering before business goes wild with it
As a quick aside there's one thing I wish SQL had that would make writing queries so much faster. At work we're using a DSL that has one operator that automatically generates joins from foreign key columns, just like
And you got clients table automatically joined into the query. Having to write ten to twenty joins for every query is by far the worst thing, everything else about writing SQL is not that bad.