Data transformation company dbt Labs has used AI to drive a variety of measurable impacts. The engineering team shipped a feature in 24 hours using an end-to-end AI development loop. One employee used Claude to build a script that assembles and creates onboarding materials, saving over 20 minutes per new customer. Another created a daily AI summary of the company’s more than 30 Slack channels, replacing a half-hour of employees’ manual scanning with a quick read.
These types of efficiency numbers are real and easy to regard as progress, but CEO and cofounder Tristan Handy believes many leaders are thinking about them all wrong. Inside his organization, he’s found that the biggest benefit from AI isn’t captured in efficiency measures or time savings, but rather in the creativity and iterative power they unlock.
As a growth-stage startup company whose technology powers the very AI transformation companies are seeking, the opportunity for dbt Labs as Handy sees it isn’t to use AI to reduce costs or slim down—it’s to seize market opportunities. AI efficiencies are the vehicle enabling the organization to take more shots, solve more problems for customers, and use those learnings to improve quality, not just increase quantity.
