Oct 18, 2026

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.

Sep 22, 2026

100x More Reliable Voice Agents

SLNG.ai introduces Unmute, an open declarative standard for voice agents, addressing platform lock-in and the limitations of current agent architectures. It proposes a shift from LLM-centric, sequential pipelines to declared execution with structural guarantees, enabling portable, cost-effective, and robust voice agents by breaking down complex interactions into modular, context-aware steps. This approach minimizes token usage, enhances determinism, and improves agent reliability compared to traditional single-prompt designs.