Voice Agent Debugging: When the Transcript Looks Fine but the Refund Goes to the Wrong Order
AI Engineer · youtube · 2026-10-06
At AI Engineer World's Fair 2026, Arize AI senior PM Fuad Ali explains why voice agents are among the hardest AI systems to debug: text logs hide latency, turn-taking failures, and transcription errors. His example: a refund call whose transcript looks fine but contained 2.4 seconds of dead air, an interruption, and a refund issued for the wrong order.
- Failure modes text misses: latency, barge-in, mishearing, and tone are invisible in transcripts
- Full tracing: open-source OpenInference semantic conventions put audio, transcript, and trace in one session view with a unified schema across providers, enabling full conversation replay
- Audio-native evals: run evals for sentiment, latency, interruptions, and task success directly on the audio, attached to trace spans
- Self-healing loop: observe → evaluate → improve, with agent experiments replaying fixes against failed traces
Docs and the OpenInference repo are publicly available.
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