Basics of Prompt Engineering AIE Practice Questions (Page 2)

Questions 6–10

1. 6expert · hard

   A customer analytics team is using an AI to generate insights from survey responses. The first prompt produced insights that were too generic and did not segment by customer type. The team needs to improve the prompt but has a strict deadline and limited time for experimentation. What is the most efficient way to improve the prompt?

   • ARun a series of experiments with different prompt variations to find the best one.
   • BUse a different AI model that is known for better segmentation.
   • CAnalyze the first output, identify the missing segmentation, and add a specific instruction to segment by customer type.
   • DAsk the AI to generate insights for each customer type separately in one prompt.
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2. 7foundation · easy

   Which of the following is a key component of a well-structured prompt?

   • AThe model's token limit
   • BThe model's training data
   • CThe model's learning rate
   • DThe expected output format
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4. 8foundation · easy

   What is the primary purpose of prompt engineering in the context of AI models?

   • ATo craft inputs that guide the AI model toward producing desired outputs
   • BTo design the underlying neural network architecture of the AI model
   • CTo train the AI model on new data to improve its performance
   • DTo create a user interface for interacting with the AI model
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5. 9foundation · easy

   Which statement best describes the role of prompt engineering in optimizing AI model outputs?

   • AIt involves adjusting the model's internal parameters to improve output quality
   • BIt shapes the model's responses by providing clear instructions and context in the input
   • CIt replaces the need for model fine-tuning in all applications
   • DIt guarantees that the AI model always produces factually correct answers
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6. 10expert · hard

   A compliance team is using an AI to summarize regulatory documents. The AI sometimes omits important compliance details. The team has a large volume of documents and needs to ensure accuracy, but they also have limited time to review each summary. What is the best way to evaluate and improve the prompt?

   • AUse a longer prompt with more context, hoping the model includes more details.
   • BManually review every summary against the original document to catch omissions.
   • CAsk the model to rate its own summary for completeness.
   • DCreate a checklist of required compliance points and instruct the model to explicitly address each one in the summary.
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