- A
Include examples of secure coding practices in the prompt.
Providing examples of secure code helps guide the model towards generating secure code.
- B
Set the max_tokens parameter to a high value to allow longer outputs.
Why wrong: Increasing max_tokens does not affect the security of the generated code.
- C
Fine-tune the model on a dataset containing examples of insecure code.
Why wrong: Fine-tuning on insecure code would teach the model to produce more vulnerabilities.
- D
Use the content filtering feature to block malicious code patterns.
Content filtering can be configured to detect and block common insecure code patterns.
- E
Add a system message that instructs the model to never generate insecure code.
Why wrong: System messages can provide guidance but do not guarantee compliance, and the model may still generate insecure code.
Quick Answer
The correct actions are to use few-shot prompting with secure code examples and to enable content filtering for malicious patterns. Few-shot prompting works by providing the model with explicit examples of secure coding practices within the prompt, leveraging in-context learning to steer the generated output toward those safe patterns without requiring model retraining. Content filtering, meanwhile, acts as a real-time safety layer that blocks outputs containing known vulnerability signatures or malicious code structures. On the AI-102 exam, this question tests your understanding of how to combine prompt engineering techniques with Azure OpenAI’s built-in safety systems, rather than relying on fine-tuning or external tools. A common trap is to assume that content filtering alone is sufficient, but the exam emphasizes that few-shot examples proactively guide the model’s behavior. Remember the mnemonic “Show and Block” — show secure examples via few-shot, and block threats via content filtering.
AI-102 Implement generative AI solutions Practice Question
This AI-102 practice question tests your understanding of implement generative ai solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A developer is using Azure OpenAI to generate code snippets. The developer needs to ensure that the generated code does not contain security vulnerabilities. Which TWO actions should the developer take? (Choose two.)
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
Include examples of secure coding practices in the prompt.
Option A is correct because including examples of secure coding practices in the prompt (few-shot prompting) directly guides the model to generate code that follows those patterns. This technique leverages in-context learning, where the model uses the provided examples to shape its output, reducing the likelihood of producing insecure code without requiring fine-tuning or external filtering.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Include examples of secure coding practices in the prompt.
Why this is correct
Providing examples of secure code helps guide the model towards generating secure code.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set the max_tokens parameter to a high value to allow longer outputs.
Why it's wrong here
Increasing max_tokens does not affect the security of the generated code.
- ✗
Fine-tune the model on a dataset containing examples of insecure code.
Why it's wrong here
Fine-tuning on insecure code would teach the model to produce more vulnerabilities.
- ✓
Use the content filtering feature to block malicious code patterns.
Why this is correct
Content filtering can be configured to detect and block common insecure code patterns.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Add a system message that instructs the model to never generate insecure code.
Why it's wrong here
System messages can provide guidance but do not guarantee compliance, and the model may still generate insecure code.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often overestimate the effectiveness of system messages (Option E) or content filtering (Option D) for code security, while underestimating the power of few-shot prompting (Option A) to directly influence model behavior through example-based guidance.
Detailed technical explanation
How to think about this question
Content filtering (Option D) works by using Azure OpenAI's built-in content moderation models (e.g., hate, violence, self-harm) but is not designed to detect code-specific security vulnerabilities like SQL injection or buffer overflows. In contrast, few-shot prompting (Option A) provides concrete examples that the model can mimic, which is more effective for code generation tasks because it directly shapes the output format and logic. Real-world scenarios often combine few-shot prompting with post-generation static analysis tools (e.g., CodeQL) to catch remaining vulnerabilities.
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.
TExam Day Tips
- 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.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement generative AI solutions — This question tests Implement generative AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Include examples of secure coding practices in the prompt. — Option A is correct because including examples of secure coding practices in the prompt (few-shot prompting) directly guides the model to generate code that follows those patterns. This technique leverages in-context learning, where the model uses the provided examples to shape its output, reducing the likelihood of producing insecure code without requiring fine-tuning or external filtering.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
This AI-102 practice question is part of Courseiva's free Microsoft 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 AI-102 exam.
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