Fuad Ali uses an AI-generated refund call to show how an apparently acceptable transcript can conceal dead air, interruption and a wrong order number. Listening to the audio alongside the tool trace reveals both the conversational failure and the incorrect action.
Fuad Ali describes a session view that links turns, audio events, tool calls and latency measurements. Shared semantic conventions can make provider-specific events easier to query, while audio-aware evaluation should examine tone, interruption, transcription drift and task success rather than treating text as the entire interaction.
Fuad Ali proposes an observe, evaluate and improve loop for voice agents, including reproducing failed interactions against candidate fixes. His account distinguishes the demonstrated tracing and evaluation workflow from a future vision of agents preparing self-healing changes for human review.
Watch on YouTube
