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In this episode, Tara Hernandez shares lessons from 18 months of AI experiments at MongoDB. As VP of Developer Productivity (or as she calls it, “VP of Kitchen-Sinkness) Tara oversees everything from CI systems to AI strategy, bringing decades of experience from Netscape, Pixar, and Google. Her team measured AI’s impact and found that it saved their developers an hour a week on coding but had zero impact on product velocity, so they kept experimenting until they found where it actually works. Rebecca and Tara talk at length about why the real wins live in the outer loop (Slack bots, log analysis, ticket generation), how to measure “people incidents” and code review bottlenecks, and why developer productivity ultimately comes down to information flow between humans, not just faster tooling. Timestamps: (00:00) Introduction (01:04) How Tara became MongoDB's first VP of Developer Productivity (06:42) Teaching Pixar how to do software development in 2002 (11:06) Tara’s three pillars of software development: 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) How 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 right now (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 Follow Tara on LinkedIn: / tara-hernandez Follow Rebecca on LinkedIn: / rmurphey Find the full transcript at swarmia.com/podcast/tara-hernandez-mongodb/