Why AI Makes You 100x Faster but Not Your Company - Mitchell Troyanovsky, Basis

Individual engineers have seen huge productivity gains from AI, but most companies haven't. Mitchell Troyanovsky, co-founder of Basis, argues that agents need to be simple and reliable to spread through a company, and the way to get there is to make them opinionated. He covers behavior specs, why outcome evals don't generalize to production, and two tools for finding out why an agent made a bad call: forking and sub-agent simulations. 0:00 Intro to Basis 0:42 Why company productivity hasn't jumped 1:41 How organizations scale with processes 3:29 The competency gap and the process gap 5:57 Agents need to be opinionated 9:02 Why outcome evals don't generalize 10:18 Example: a bank reconciliation behavior 12:03 Behavior specs 13:24 Forking to diagnose bad decisions 15:15 Simulations with sub-agents 17:10 Earning trust like a coworker 18:10 Why not let agents find a better way? Mitchell Troyanovsky, co-founder of Basis Join us in SF for the second annual AIE CODE summit: https://aie.codes our last flagship summit of 2026. Applications live now!