Evaluating Agent Performance Beyond Matching | Dataford Interview Questions

Scenario

You are evaluating an AI agent that retrieves context, uses tools, and produces multi-step answers. Exact string matching is clearly too narrow because the agent can succeed with different wording, partially fail in retrieval, or take an inefficient tool path while still sounding correct.

Question

How do you evaluate the performance of an AI agent beyond simple output matching (e.g., using RAGAs or custom evaluation frameworks)?

Problem

Scenario

Question

How do you evaluate the performance of an AI agent beyond simple output matching (e.g., using RAGAs or custom evaluation frameworks)?

Problem

Scenario

Question

How do you evaluate the performance of an AI agent beyond simple output matching (e.g., using RAGAs or custom evaluation frameworks)?

Problem

Scenario

Question

How do you evaluate the performance of an AI agent beyond simple output matching (e.g., using RAGAs or custom evaluation frameworks)?