With great context comes great autonomy: leveling up your agent context
An agent is about to query your warehouse to answer a question, with total confidence and zero doubt. Thanks to dbt structured context — governed models, tested metrics, the dbt Semantic Layer — it's not guessing anymore. It knows what "active" means, which revenue table to trust, what the business logic says. dbt structured context hands your agent a map, and every road on it leads somewhere real.
But a map only shows the roads someone has already built. Leveling up means giving agents the freedom to reason beyond fixed definitions, pulling in whatever structured or unstructured context actually answers the question at hand. In this session, we'll show a live demo of the dbt structured context and Fivetran context layer turning raw metadata, governed semantic models, and real usage into the agent schema that powers accurate results, using the tools you already run: Fivetran and dbt.
Check out more sessions
- Breakout session
From AI experiment to production: how Okta governs context for agents at scale
Pooja Crahen / OktaView session - Roundtable
Product roundtable: dbt Wizard: your AI teammate for data development
Ani Venkateshwaran / dbt LabsBrandon Thomson / dbt LabsView session - Breakout session
From backend PR to dbt model: The merge request with no human in the loop
Abdullah Zia / Pet Media GroupView session
