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How KOHO built a Claude-powered self-serve analytics tool on years of dbt governance
KOHO explains why AI self-serve analytics needs a strong data culture and a governed dbt foundation first.
Why most of your dbt models aren't in a hurry, and what that's worth in Snowflake credits
Most models in a dbt DAG aren't on the critical path. Espresso AI and Authentic Insurance on turning that slack into real savings.
How Checkr cut an hours-long metrics investigation to minutes by engineering AI context on dbt and Omni
Checkr gave its AI agent a structured dbt context layer, cutting a support-metric investigation from hours to minutes.
How KOHO built a Claude-powered self-serve analytics tool on years of dbt governance
KOHO explains why AI self-serve analytics needs a strong data culture and a governed dbt foundation first.
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%.
How Ramp's internal AI agents crossed a million sessions
Ramp shares the agents, sandboxes, and dashboards it built by treating internal AI as analytics engineering.
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.