AI-103 Certification Practice Question #43

Question

Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
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You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
Users report that some responses omit required regulatory clauses, even when the clauses are present in the retrieved content.
You need to improve response completeness.
Solution: You increase the value of the temperature parameter.
Does this meet the goal?

Accepted Answer

Temperature governs how deterministic the model's token selection is: low values make output focused and repeatable, high values make it more varied and creative. Neither setting controls whether the model includes a specific required clause from the retrieved context. Increasing temperature would, if anything, make completeness *worse* by adding randomness to what the model emits. The completeness problem is solved by verification/grounding (Q42), not by sampling temperature, so the solution does not meet the goal. The official Suggested Answer (B/No) confirms this. Confidence is held at 88% — strong conceptual and official-key support, but no community votes in the file to corroborate.

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