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Across the data and AI industry, infrastructure that once served dashboards and human analysts is being rebuilt to serve autonomous agents instead. That shift changes what "AI-ready data" actually means, pushing teams to rethink documentation, governance, and the semantic layer so agents pull consistent, trusted definitions rather than guessing. Day to day, this shows up as pressure to clean up gold-layer tables, eliminate duplicate metrics, and formalize business logic that used to live only in someone's head. It raises real questions: how clean does data need to be before agents can safely act on it, and who ends up owning that definition?
Tristan Handy is President and Co-Founder of Fivetran + dbt Labs, the company formed by the June 2026 merger of Fivetran and dbt Labs. He founded dbt Labs in 2016 (originally as Fishtown Analytics) and spent a decade as its CEO before leading the company through the merger, and has worked in data for 23 years.
In the episode, Richie and Tristan explore the dbt and Fivetran merger, building an open and modular data stack, using data to power trustworthy AI agents, the growing importance of semantic layers, how data team structures are evolving, career advice for data practitioners, context engineering for AI-driven research, and much more.
Links Mentioned in the Show:
• LookML / Looker's semantic layer
• The Vaccine Education Center (CHOP)
• AI-Native Course: Intro to AI for Work
- Related Episodes:
- The Data Team's Agentic Future, with Ketan Karkhanis, CEO at ThoughtSpot
- Towards Self-Service Data Engineering with Taylor Brown, Co-Founder and COO at Fivetran
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