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Feedback

As explained in Build an AI Agent (From Scratch)

End-user feedback is information about system quality or satisfaction provided by people who interact with the deployed system.

End-user feedback is information about system quality or satisfaction provided by people who interact with a deployed system. In agent evaluation, it is one evaluator category alongside code-based evaluators, LLM judges, and human evaluators. section 10.3

Use end-user feedback as part of a broader evaluation approach:

  • Combine it with other evaluation methods when validating agents whose prompts, models, or data change. section 10.3
  • Treat it as a signal grounded in people’s interactions with the deployed system. section 10.3

How Build an AI Agent (From Scratch) covers it

How deep it goes
Defines feedback as an evaluator category but does not specify collection procedures, metrics, or implementation details.
What you can do after
Evaluate deployed-system quality or satisfaction using information supplied by interacting users.
How it connects
Connects end-user feedback to agent evaluation, code-based evaluators, LLM judges, and human evaluators.

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This explainer was generated by Manning's knowledge graph from the text of Build an AI Agent (From Scratch). The section links point to the parts of the book it draws on.