Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A company uses Azure OpenAI Service to generate marketing copy for a new product. They have a strict brand voice that requires formal, technical language and explicitly prohibits any humorous or informal phrases. They want to enforce these constraints without retraining the model. Which technique should they use?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
A) Fine-tuning
Fine-tuning involves retraining the model on a specific dataset, which requires additional labeled data and compute resources. The scenario explicitly states they want to avoid retraining.
B
Best answer
B) Prompt engineering
Prompt engineering designs the input prompt to control the model's output characteristics, such as tone, style, and content. This is a lightweight, no-training approach to enforce brand voice constraints.
C
Distractor review
C) Reinforcement learning
Reinforcement learning trains a model by rewarding desired behaviors. It is typically used for training from scratch or fine-tuning, not for applying constraints in a single prompt.
D
Distractor review
D) Transfer learning
Transfer learning is a broader concept of using a pre-trained model and adapting it to a new task. It usually involves fine-tuning, which is not the requested approach.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A developer wants to build a virtual assistant that can understand user intents such as 'Book a flight' or 'Check weather' and extract relevant entities like destination and date. The developer has a small set of labeled example utterances. Which Azure AI Language feature should the developer use?
Question 2
A developer is building a customer support chatbot using Azure OpenAI. The chatbot should never reveal its system instructions or internal configuration. The developer wants to add a rule at the beginning of the conversation to prevent prompt injection attacks. Which technique should they use?
Question 3
A developer is using Azure OpenAI Service to generate product descriptions from technical specifications. The generated descriptions sometimes include plausible-sounding but incorrect details (hallucinations). The developer wants to ensure the model's responses are strictly based on the provided product data and does not add any external or invented information. Which approach should the developer use?
Question 4
A developer is using Azure OpenAI with GPT-4 to build a chatbot that answers legal questions based on a company's internal policy documents. The developer wants the model's responses to be maximally deterministic and factual, avoiding any creative or speculative language. Which parameter should the developer set to the lowest possible value in the API call?
Question 5
A developer is using Azure OpenAI to generate creative product descriptions. The outputs are often repetitive and lack variety. The developer wants to increase the diversity of the generated text while still keeping it coherent. Which parameter should the developer increase?
Question 6
A developer is using Azure OpenAI Service to generate product descriptions. They want the output to be highly focused and deterministic, with less randomness. Which parameter should they decrease?
FAQ
Questions learners often ask
What does this AI-900 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: B) Prompt engineering — Prompt engineering involves crafting the input prompt to guide the model's output style, tone, and content without modifying the model itself. By including instructions like 'Write in a formal, technical style. Do not use humor.' the desired constraints can be achieved. Fine-tuning would require retraining on labeled data, which is not desired. Reinforcement learning is for training from rewards, and transfer learning is about using a pretrained model as a starting point. Therefore, prompt engineering is the correct technique.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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