ML Summer School 2026 - Evaluations with Laurie Voss

Description

​How do you know if your LLM application is actually working, and how do you catch it when it isn't? This hands-on session walks through the practical mechanics of evaluation and observability for production AI systems. Using Arize, we'll cover how to instrument your application, trace what's happening across multi-step and agentic workflows, set up evals that catch failures, and use feedback from evals to automatically improve your app. You'll leave with a concrete picture of what production-grade evaluation looks like in practice. This session is hosted as part of Cohere Labs Open Science Community's ML Summer School. At Cohere Labs Open Science Community, we believe the future of machine learning isn’t gated by credentials, borders, or budgets, it’s built in open collaboration, powered by curiosity, and made stronger through community. This summer, we’re excited for the return of Cohere Labs Open Science Community Summer School, a learning initiative featuring some of the leading minds in machine learning from Meta, Google DeepMind, Cohere Labs and more. This initiative reflects the core mission of Cohere Labs: supporting fundamental research, expanding access, and enabling the next generation of ML thinkers — regardless of where they start. We are very grateful to our community leads for organizing this series of events!