If your model’s accuracy suddenly drops by 10% on Tuesday, how do you determine if the Model changed (API update), the Data changed (new documents in RAG), or User Behavior changed?

Explain the concept of using a "Stronger" model (like GPT-4o or Claude 3.5 Sonnet) to grade a "Weaker" model’s output. What are the risks of "Self-Preference Bias" in this setup?

If you are using an LLM to grade another LLM, why is it critical to provide a "multi-point rubric" rather than just asking "Is this answer good?"

You’ve updated your system prompt to fix a specific bug. How do you ensure this "fix" didn't break 10 other things the model was previously doing correctly?