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How to put generative AI directly into a dbt pipeline with plain SQL
Google Cloud on wiring BigQuery's AI SQL functions into dbt pipelines, from sentiment scoring to LLM-generated product briefings.
Why an AI agent's revenue query was $3.5 million wrong, and how AWS fixed it with dbt Semantic Layer
A plausible AI revenue query was $3.5 million wrong. AWS explains how business context helps prevent those errors.
Ship AI agents like tables: dbt materializations for Snowflake CoWork
Under Armour turned Snowflake AI agents into dbt models, giving every agent the same review and CI process as every table.
dbt v2 lands: faster parsing, one shared adapter layer, and a docs experience that skips the giant manifest.json
dbt v2 bundles adapters, speeds up parsing, and replaces manifest.json with smaller, queryable files for people and AI.
Showing our work: a controlled experiment in context engineering
We ran one AI skill 80 times against four context sources. Engineered summaries cut cost 48.5% and run time 43.2%.
From prompt to PR: how Careem’s AI writes and validates dbt models before a human ever sees them
Careem's AI agent writes and validates dbt models end to end before a human ever reviews the PR.