AI Evals Platform for Cross-Functional Teams at Scale

Official Schedule Context

DoorDash's Evals Platform is designed for more than just engineers. It brings human review,

automated judges, and online experimentation into a single calibration loop so engineering, product

managers, and strategy and operations teams can all contribute to improving AI quality. Engineers

can instrument, trace, and evaluate agent behavior, while cross-functional teams can review outputs,

curate trusted examples, and provide structured feedback that improves how automated judges behave

over time. By combining experimentation, fully customized annotation workflows, calibration, and

analytics in one system, the platform turns AI quality from a fragmented technical exercise into a

shared operating model for continuously improving agent performance and making rollout decisions

with confidence. While vendor platforms offer pieces of this workflow, we needed something broader:

a unified system that lets engineers, product managers, and Strategy & Ops all participate directly

in improving AI quality. Our goal is not just to run evals, but to enable cross-functional teams to

review outputs, calibrate judges, run experiments, and make rollout decisions without being blocked

on engineering. That requirement, along with tighter integration into our internal workflows and

operating model, is why we are building this platform in-house.

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

Pending transcript synthesis when an official recording or confirmed matching video is available.