Why AI Alone Can’t Fix Your Sh*tty Data Models w/ Kyle Nesbit (Credible Data)
In this episode of The Joe Reis Show, I sit down at my house in Salt Lake City with Kyle, founder of Credible Data. Before founding Credible, Kyle spent nearly 17 years at Google building core distributed systems—including the in-memory shuffle/join backplane that powers BigQuery—before moving to Gradient Ventures and spending four years helping integrate Looker into GCP. We dive deep into the reality of semantic layers, the origins of Malloy, and why the current hype around semantic layers often misses the mark. Kyle breaks down why SQL conflates data modeling and queries, how agents are shifting data work from painful bottom-up ETL to deterministic top-down domain modeling, and why giving an LLM an entire enterprise schema creates nothing but "data slop." We also get into the future of data engineering, what analysts should actually be learning today, and why unlocking the "long tail" of dark business data is where the true value lies. Connect with Kyle & Credible: credibledata.com Guest policy: The Joe Reis Show is strictly invite-only. Unsolicited guest pitches, PR agency solicitations, and booking requests are not accepted or reviewed.