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JevMade field notes / Scorer walkthrough

Check if an AI support reply is ready to send

You will learn how to use an AI tool called Jev to grade draft customer support messages. The guide explains how to set up categories to catch bad advice and save the results for human review.

Original by Izzy HurleyEvaluation

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Credits

“Eval agent responses with Jev” by Izzy Hurley. Read the original source.

This expanded guide is an AI-narrated adaptation prepared by JevMade. It expands the source’s essential ideas, examples and caveats in JevMade’s own words and is not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

Our summary

The author shows how to check if an AI assistant wrote a good customer support message. Instead of writing a new answer, an AI tool called Jev chooses from a list of options. This helps businesses catch unsafe or incomplete drafts before they reach a real person.

You give the software the customer request, the true facts, and the draft reply. The tool picks the best category, like whether the reply is ready to send or needs work. The system saves this choice along with a score showing how certain the software was.

This setup is useful for teams managing automated messages, but the certainty score does not guarantee the choice is correct. You must test the tool with your own examples to find a good cutoff point for asking a human to check the work.

Key takeaways

  1. Group the customer request, the true facts, and the draft reply together for the software to review.
  2. Create clear categories for unsafe claims, incomplete answers, and messages that are ready to send.
  3. Save the software certainty scores to help you decide which messages need a human to check them.

You need a private access code for TypeSafe or special permission in Braintrust to use this. The reviewer did not run the scoring tool or the tracking software to verify the author claims.

Braintrust blog · Source reviewed · Original published

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