Building Reliable AI Features
This talk explores how to build reliable, production-grade AI features in an environment where outputs are probabilistic and models can change without notice. It covers practical strategies for observability, eval testing, and model version control to detect drift, measure performance, and maintain user trust as AI systems evolve.
