In this episode, Tara Hernandez shares what 18 months of rigorous AI experimentation taught her at MongoDB — including why the initial results showed negative ROI, and where her team eventually found the real productivity wins.

Tara explains how AI saved developers an hour a week on coding but had zero impact on product velocity, why the unglamorous outer loop improvements (Slack bots, log analysis, ticket generation) deliver bigger impact than code generation, and how developer productivity ultimately comes down to information flow between humans.

She also gets into why developer experience matters more now than during the hiring frenzy, and why curiosity is what defines good developers.

(0:00) Introduction
(1:04) How Tara became MongoDB’s first VP of Developer Productivity
(6:42) Teaching Pixar how to do software development in 2002
(11:06) Tara's three pillars of developer productivity: tools, communication, and process
(18:52) How the internet changed infrastructure from “not real engineering” to essential
(22:00) MongoDB’s 18-month AI journey: from skepticism to scientific measurement
(25:11) The surprising truth: AI saved coding time but had zero impact on velocity
(27:03) Where AI actually wins: senior engineers with agentic programming
(30:04) What developer productivity teams should focus on in the AI era
(34:14) Why the outer loop matters more than the inner loop
(37:08) Measuring the cost of human-to-human communication
(40:14) Developer productivity is really about information flow
(41:13) Why developer experience matters more now, not less
(44:33) The ethical problem with celebrating AI-driven layoffs

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Find the full transcript on the Swarmia website