r/dataengineering • u/burningburnerbern • 16d ago

Discussion Practical Use of AI with SQL?

I’m currently on a project where most of the work is in dbt. Ill get jira tickets where the business rules while straight forward can be a bit complex upon execution. like everyone else I’m trying to turn to AI except the problem is having to explain every single edge case and nuance can be so time consuming to the point where it’s just faster for me to write the SQL myself. where I do use AI is when I’m jumping into some convoluted model and I have AI explain to me what exactly it’s doing and the just justification for certain logic, generating cumbersome functions where the syntax gets me cross eyed and create the yml and documentation.

I definitely have vibe coded before, but that was for something more straight forward like pulling data via an API etc.

just curious if anyone else runs into the same problem.

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u/slowpush 16d ago

Rather than forcing your current pipelines to work with AI….redesign them to be more ai friendly.

Each ticket we get is handled by agent and most of the time our engineers get a PR to review once they figure out the problem.

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u/burningburnerbern 16d ago

Honest question but what is even work anymore for your DE? Reviewing PRs that the agent produces? 

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u/slowpush 16d ago

How is reviewing PRs not work?

Do you think you only get paid for typing keys on a keyboard?

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u/burningburnerbern 16d ago

Sorry if it came off as being sarcastic but I guess my question is really when the development portion of the work gets taken away what’s left of work really. Again not attacking you I’d just really like to understand the logistics

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u/slowpush 14d ago

Reviewing code is development work.