Databricks-GenAI-Assoc Application Development Practice Question
An engineer is using Mosaic AI Agent Evaluation to score a conversational agent that calls tools. The agent sometimes answers correctly but with fabricated citations. Which evaluation approach best surfaces this specific failure mode?
⚠ Common exam trap
The trap here is conflating answer correctness with grounding, assuming that a factually right answer cannot also contain a fabricated citation.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable the groundedness judge and supply the retrieved context so the judge can verify claims against sources.
The groundedness judge compares response claims against the retrieved context, which is precisely how fabricated citations are detected. A correctness judge evaluates answers against references and misses unsupported citations, operational metrics say nothing about grounding, and removing tools avoids the scenario rather than evaluating it.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Measure only token usage and latency to detect when the agent is hallucinating citations.
Why it's wrong here
Token usage and latency are operational metrics that reveal cost and performance, not factual grounding. A hallucinated citation may consume the same tokens and time as a legitimate one. These metrics cannot distinguish supported from fabricated claims, so they are unsuitable for this diagnostic goal.
- ✗
Run the agent without tools so it cannot produce citations at all.
Why it's wrong here
Removing tools eliminates the agent's ability to retrieve and cite sources, which changes the application's behavior rather than evaluating it. The goal is to detect fabricated citations in the real system, not to prevent citation generation. This approach sidesteps the requirement instead of measuring it.
- ✓
Enable the groundedness judge and supply the retrieved context so the judge can verify claims against sources.
Why this is correct
The groundedness judge checks whether statements in the response are supported by the provided context. Fabricated citations are exactly the failure mode it detects, because the cited source either does not exist in the context or does not contain the claim. Supplying the retrieved context is required for the judge to perform this verification accurately.
- ✗
Rely solely on the correctness judge, since a correct answer cannot contain fabricated citations.
Why it's wrong here
A response can be factually correct yet cite a source that was never retrieved, which the correctness judge does not catch because it evaluates the answer against a reference rather than against the retrieved context. Fabricated citations are a grounding problem, so a correctness-only evaluation misses the failure mode entirely.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-GenAI-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-GenAI-Assoc exam.