FIELD NOTES

Building A Voice Agent Prompt That Passes The Handoff Test

The handoff test: can a human pick up mid-call from the AI transcript and not lose the customer? Here is the prompt architecture that passes it 94% of the time.

How the post opens

A human picks up mid-conversation from the AI transcript. Can they continue the call without losing the customer? If the AI did not capture intent, context, and emotion in the transcript, the human starts from scratch and the customer feels it. Here is the prompt architecture that passes the test 94 percent of the time. The tradeoffs we made and why Every architecture choice in this category is a tradeoff.

What it argues

The tradeoffs we made and why Every architecture choice in this category is a tradeoff. Here are the ones we have made consciously, and the alternative we did not pick. We use Pipecat instead of building our own orchestration. The win is months of saved engineering. The cost is being a release behind on a few model integrations.

Filed under

Why this one exists

The handoff test: can a human pick up mid-call from the AI transcript and not lose the customer? Here is the prompt architecture that passes it 94% of the time. It is filed under AI Voice because that is where operators looking for this problem actually start, and it is written from production work rather than from a content calendar.