How do you measure groundedness for a RAG system or an AI agent?

Tanishq's recipe in Gaurav Sen's AI interview #4 uses the user query, the bot's response, the system prompt and one extra input: the context the bot used to answer. In a RAG system that context is the retrieved chunks, such as the top five. For an agent it is the tool responses, plus any reasoning the model produced. High groundedness means the agent is following that context properly.

• Answer relevancy needs only the query, the response and optionally the system prompt.

Source: our own transcription of the episode. The full conversation is on Gaurav Sen (2026-08-12). Read the whole episode summary →

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