topic Configuring Genie: practical steps for more reliable answers in Get Started Discussions

Configuring Genie: practical steps for more reliable answers

arthurfr23 — Fri, 25 Sep 2026 15:14:05 GMT

I published a hands-on guide to preparing and testing a Genie Agent, using a small sales dataset with known results

A few practices covered:

Define table grain and relationships to avoid inflated totals after joins.
Document metric definitions, currencies, and date semantics.
Add reviewed SQL examples for recurring questions.
Create benchmarks with expected results and rerun them after configuration changes.

The article includes SQL setup, sample instructions, and validation scenarios.

https://medium.com/@arthurfr23/databricks-genie-a-practical-guide-from-tables-to-tested-answers-aa91dff98587

What has been your biggest challenge with Genie: business context, joins, or validating answers?

Re: Configuring Genie: practical steps for more reliable answers

Khasim_1 — Sun, 27 Sep 2026 17:13:12 GMT

Great guide, Arthur! I particularly agree with your point on defining table grain and relationships—those are often the silent killers of 'Genie' accuracy, especially when joins inflate totals. In my current work with complex medallion architectures, the biggest hurdle hasn't just been the join logic, but ensuring the 'semantic layer' remains consistent as business definitions evolve. Do you have a preferred method for managing 'Gold' layer metric definitions so that the Genie agent doesn't drift when the underlying business logic changes?

Re: Configuring Genie: practical steps for more reliable answers

arthurfr23 — Tue, 29 Sep 2026 13:35:22 GMT

Great Khasim!

In general, I used a contract (in yml or json) with this rules and Genie can see this documents for understanding. But I'm had saw in others scenarios some people using a control table to register this logics too.