At Waymo, an AI project isn't ready until its evals are — not when the model performs well

Few companies face higher stakes when deploying AI than Waymo, the self-driving car company under Alphabet that spun out of Google. Its models do not merely generate text or automate back-office tasks: They help vehicles navigate unpredictable streets, respond to human drivers and make split-second decisions in the physical world.But the methods Waymo uses to manage those risks — continuous evaluation, carefully curated data, human oversight and clearly defined business outcomes — offer a broader playbook for enterprises deploying AI agents in nearly any industry.Manasi Joshi, Waymo’s director of engineering for systems intelligence and machine learning, explained at VB Transform 2026 how the autonomous vehicle company trains, tests and deploys AI at scale. To date, Waymo has driven more t…