Bryan Bischoff

Hamel Husain, a machine learning engineer and evals expert, discusses the pitfalls of AI evaluations and how to adopt a data-centric approach for reliable results. He outlines ten critical mistakes teams make, debunking ineffective metrics like 'hallucination scores' in favor of tailored analytics. Hamel shares a workflow for effective error analysis, including involving domain experts wisely and avoiding hasty automation. Bryan Bischoff joins as a guest to introduce the 'Failure as a Funnel' concept, emphasizing focused debugging for complex AI systems.