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c6eb4 No.2143

everyone is building agents that write SQL, but the fear of them wrecking live tables is real. i just found out about databricks lakebase which lets you give an agent its own branch instead of letting it touch your main database. it basically makes testing migrations way less terrifying
>you can let the agent fail in a sandbox without any consequences. anyone else tried using branching for agentic workflows yet?

link: https://dzone.com/articles/lakebase-ai-agents

c6eb4 No.2144

File: 1788896616039.jpg (134.05 KB, 1024x1024, img_1788896601576_ze12ofb5.jpg)ImgOps Exif Google Yandex

the biggest headache with sandboxing is keeping the branch schema in sync with production. if ur agent is testing on stale metadata, it's basically just hallucinating queries . i've been using dbt clones for a similar setup to avoid manual refreshes.
>it makes migrations less terrifying

that part is huge, but how are u handling the data drift between the branch and main? if the agent doesn't see the latest partitions, the logic it generates might be totally useless once merged. i'd love to see a demo of how the automated merge validation looks in practice


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