OCI 1Z0-1127-25 Sample Questions with Explanations

These original sample questions are designed to help you check how the exam topics appear in decision-style prompts. They are not taken from the live exam.

Use these sample questions as a guided self-assessment for OCI Generative AI Professional (1Z0-1127-25) topics such as retrieval grounding, model/service fit, prompt behavior, safety controls, evaluation, deployment responsibility, and data handling. The prompts focus on design decisions rather than generic AI definitions.

Where these questions fit in the 1Z0-1127-25 guide

The sample set below is part of the Oracle OCI Generative AI guide path:

• Oracle certification hub
• OCI guides
• 1Z0-1127-25 exam guide
• 1Z0-1127-25 cheat sheet
• 1Z0-1127-25 study plan
• 1Z0-1127-25 FAQ
• 1Z0-1127-25 resources
• 1Z0-1127-25 glossary

1Z0-1127-25 OCI GenAI sample questions

Work through each prompt before opening the explanation. For generative AI questions, separate prompt behavior, grounding, model capability, access control, and operational responsibility.

Question 1

Topic: Grounding a policy assistant

A company wants a chatbot to answer HR policy questions using only the current employee handbook. The model sometimes gives plausible answers that are not in the handbook. Which design change most directly addresses the issue?

• A. Increase temperature so the model can explore more possible answers.
• B. Add retrieval from the approved handbook content and instruct the model to answer from retrieved passages.
• C. Remove source documents so the model relies only on pretraining.
• D. Use a longer welcome message before each conversation.

Best answer: B

Explanation: Retrieval grounding anchors answers to approved source material. For policy questions, the key design move is to fetch relevant handbook passages and constrain the response to that context.

Why the other choices are weaker:

• A can make output more variable, not more source-grounded.
• C removes the current business source of truth.
• D does not solve source selection or factual grounding.

What this tests: Retrieval, grounding, source-of-truth design, and hallucination-risk reduction.

Related topics: Grounding; Retrieval; RAG; Policy assistant

Question 2

Topic: Prompt fix versus data fix

A retrieval-based answer flow frequently misses relevant documents because the search index contains outdated and duplicated chunks. Which fix should come before prompt tuning?

• A. Rewrite the prompt to be more enthusiastic.
• B. Clean and refresh the indexed content, improve chunking, and retest retrieval quality.
• C. Disable retrieval so the model does not see conflicting sources.
• D. Increase maximum output length for every response.

Best answer: B

Explanation: If retrieval quality is weak because the indexed content is stale or poorly chunked, prompt changes are secondary. The system needs better context before the model can produce reliable grounded answers.

Why the other choices are weaker:

• A changes style, not retrieval correctness.
• C removes the grounding path rather than fixing it.
• D affects response length, not source selection.

What this tests: RAG troubleshooting, content preparation, retrieval quality, and prompt/data responsibility boundaries.

Related topics: Retrieval quality; Chunking; Prompt tuning; Troubleshooting

Question 3

Topic: Access control for GenAI output

A GenAI assistant can retrieve documents from multiple departments. Users should only receive answers based on documents they are allowed to access. Which architecture choice best supports that requirement?

• A. Apply user-aware authorization before or during retrieval so unauthorized documents are not used as context.
• B. Retrieve all documents and ask the model not to reveal restricted information.
• C. Hide citations while allowing the model to use every document.
• D. Use a single shared service account with unrestricted document access for all users.

Best answer: A

Explanation: Access control must be enforced before restricted content becomes model context. If the retrieval step includes unauthorized documents, the system has already crossed the data-boundary line.

Why the other choices are weaker:

• B relies on prompt compliance after exposing restricted context.
• C hides evidence but still allows restricted content to influence output.
• D removes user-level authorization and increases data exposure risk.

What this tests: Security boundaries, retrieval authorization, least privilege, and GenAI data handling.

Related topics: Access control; Security; Retrieval; Data boundaries

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