Meet the Evaluations framework

A Podkey summary of Meet the Evaluations framework, from WWDC 2026.Today’s thread is really about a simple problem with messy consequences: AI features don’t behave like ordinary software, so ordinary testing stops being enough pretty quickly. The big idea here is an Evaluations framework that measures how often an AI system does the right thing, how often it drifts, and how developers can use that feedback to steadily tune prompts, judges, and datasets into something more reliable. And what makes this interesting is that it’s not just about catching failures. It’s about building a practical loop for improving AI behavior on purpose instead of squinting at a few outputs and hoping for the best.Why normal tests break downHow the framework is set upA very simple metric that tells you a lotHill climbing with promptsUsing a model to judge another modelScaling up with synthetic dataThe development loop that emergesBest practices that keep this manageableThis podcast was created with Podkey. Make your own at https://podkey.fm