Evals for High-Stakes AI Agents — Doneyli De Jesus & Annabell Schäfer, Langfuse

A hands-on workshop from Langfuse on evaluating AI applications where mistakes are costly. Using a banking assistant as the running example, Annabell Schäfer and Doneyli De Jesus walk through the AI engineering loop: tracing with PII masking, building datasets, turning domain-expert comments into failure modes, mixing LLM-as-a-judge and code evaluators, and CI gates that block prompt changes when scores drop.