The automation need: prompting for correct SQL and pandas, and wiring LLM steps into pipelines that clean, triage, and self-heal.
How to catch renamed and reordered upstream columns automatically without letting a language model silently corrupt your schema.
Generated pandas aggregations often run clean and return the wrong number; here is how to prompt and verify so the logic is actually right.
A read-only triage agent that classifies why a dbt or Great Expectations test failed and routes it, without ever touching your data.