AIF-C01 Question #126: Real Exam Question with Answer & Explanation

Question

A company wants to use a large language model (LLM) to generate concise, feature-specific descriptions for the company's products. Which prompt engineering technique meets these requirements?

Options

• ACreate one prompt that covers all products. Edit the responses to make the responses more
• BCreate prompts for each product category that highlight the key features. Include the desired
• CInclude a diverse range of product features in each prompt to generate creative and unique
• DProvide detailed, product-specific prompts to ensure precise and customized descriptions.

Explanation

To generate concise, feature-specific product descriptions using an LLM, the company should categorize products and highlight key features in prompts.

Common mistakes.

• A. A single prompt for all products would likely lead to generic or inconsistent descriptions requiring significant manual editing, which is inefficient and counterproductive for specific needs.
• C. Including a diverse range of features in each prompt might make the descriptions overly broad, less concise, and potentially dilute the focus on specific, important features.
• D. While detailed, product-specific prompts ensure precision, they might lead to very lengthy and less concise descriptions, potentially overcomplicating the input for generating just "concise, feature-specific" outputs.

Concept tested. Prompt engineering for specific output

Reference. https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/prompt-engineering

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