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Collect Feedback

Real quality work starts after the channel is live.

The goal is not to make stakeholders diagnose the agent. The goal is to let them point at the exact message that felt wrong, then let the operator and Copilot do the structured follow-up.

Step 1: Ask stakeholders to leave feedback on the exact reply

In the published web client, the stakeholder can click Improve directly on the agent message that needs work.

They do not need to explain the root cause. A short natural-language comment is enough, such as:

  • This is too generic.
  • It should recommend a callback sooner.
  • It missed the difference between first visit and follow-up.

Stakeholder leaving Improve feedback on the exact reply

Positive feedback still helps, but Improve is what creates the most actionable trail for operators.

Step 2: Review the feedback record in Histories

Once feedback is submitted, open Histories and inspect the same thread in context.

You are looking for:

  • the exact user request
  • the exact reply that triggered the feedback
  • the stakeholder comment
  • whether this looks like a one-off miss or a pattern worth protecting

Feedback recorded inside the history thread

Step 3: Ask Copilot inside the thread

From the history page, open Copilot and ask what likely caused the behavior.

This is usually the fastest way to separate:

  • an instruction problem
  • a tool trigger problem
  • a knowledge gap
  • a long-thread consistency problem

Operator asking Copilot about the exact thread and feedback

Step 4: Fix the agent, then protect the case

After you update the agent and confirm the fix works, go back to the same history thread and click Add Case.

That turns the risky conversation into something you can keep testing in Test Suite.

Turning a real conversation into a reusable case with Add Case

What good stakeholder feedback looks like

Ask stakeholders for comments that are:

  • attached to the exact reply
  • short and concrete
  • written from their point of view, not as prompt-engineering instructions

Good examples:

  • This answer sounds too certain.
  • I still don't know which consultation to choose.
  • It should have asked one more clarifying question before recommending anything.