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What are agent traces in AI observability?

Answered from AI Interview Questions #4 - Evals in AI · Gaurav Sen · 2026-08-12

Tanishq describes agent traces in Gaurav Sen's AI interview series as the agent-era version of logs. A trace stores changes to the system prompt, which tools were called and how many times for a query, each tool's response, and the decision the model made from that response. The point of storing them is to evaluate the agent later, since evals cannot run without this record.

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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Q1How do you make an LLM application reliable, according to Gaurav Sen's AI interview #4?Q3What are evals for AI agents, and how are they different from unit tests?Q4Which eval metrics does Tanishq recommend for an AI agent on Gaurav Sen's channel?Q5How do you measure groundedness for a RAG system or an AI agent?
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