Lyft

Build Evals That Actually Matter - Nick Ung, Lyft

Jul 19, 2026 · 37:45

Nick Ung and Akshay from Lyft explain how to build evals that actually matter for customer-support AI agents, sharing their end-to-end pipeline. They argue offline evals must use a fine-tuned user simulator trained on real rider and driver transcripts to produce messy, frustrated behavior—not an off-the-shelf LLM that sounds too nice. Their LLM judge is treated as a binary classifier, calibrated against human labels using precision and recall, with metrics tied to actionable business outcomes like escalation decisions. They detail a continuous error-analysis loop that feeds production failures back into the offline test set and closes the loop through context, harness, or model learning. The talk also previews their config-driven eval harness with YAML primitives for tasks, datasets, and personas, enabling repeatable runs across development stages.

Taste & Craft: A Conversation with Tuomas Artman, CTO Linear & Gergely Orosz, @pragmaticengineer

Apr 21, 2026 · 29:17

Tuomas Artman, CTO of Linear, warns that AI's ability to instantly ship features risks creating convoluted, low-quality software, arguing that taste and design must guide development. He explains Linear's culture of deliberate product decisions, including a 'zero bug policy' where bugs are fixed within hours, and 'Quality Wednesdays' where engineers find and fix one minute detail each week—resulting in over 2,500 quality fixes. Artman notes that AI lacks human 'taste' and cannot feel user experience nuances like animation timing. He predicts all software engineers will become product engineers, needing to focus on customer needs and UX, and advises aspiring product engineers to build for themselves, talk to customers, and study Apple's Human Interface Guidelines.