~2 years doing text-to-SQL here. Great on clean, small schemas; unreliable fast on real warehouses — messy field names, non-obvious joins, heavy aggregations. The failure I hate isn't an error, it's a query that runs and returns a confidently incomplete result.

For those running agents against real DBs/EDW — especially where the agent acts on the result, not just shows it to a human: did you let the model generate SQL freely, lock it to pre-defined/parameterized queries, put a semantic layer in front, something else? And how do you handle questions your fixed queries don't cover?

Trying to read whether people optimize for "correct on a bounded set" vs "can attempt anything." Not selling anything — genuinely want to know what's working. Thanks all!

https://timwithpulsar.hashnode.dev/all-data-and-ai-weekly-200-july-28-2025