NCP-GENL Prompt Engineering Practice Question
Exhibit
System: You are an expert at summarizing NVIDIA technical whitepapers. User: Summarize the latest Grace Hopper Superchip architecture. Assistant: [Model generates a 500-word response] Issue: The response includes generic marketing fluff and lacks the requested technical depth.
Refer to the exhibit. Which prompt engineering technique would best force the model to prioritize technical detail over marketing language?
⚠ Common exam trap
Candidates frequently choose vague instructions like 'be more technical' instead of providing specific, actionable constraints, failing to realize that LLMs require explicit structural boundaries to filter out marketing-heavy language.
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
✓
Add a constraint: 'Exclude marketing language and include specific architectural metrics like TDP, memory bandwidth, and interconnect speeds.'
The model is failing to adhere to the implicit expectation of 'technical depth.' By explicitly defining a structural constraint—such as requiring specific architectural metrics or removing marketing terminology—the model is forced to prioritize the technical aspects requested. This type of constraint-driven prompting is essential for professional NVIDIA technical writers and engineers who need precise documentation summaries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Add a constraint: 'Exclude marketing language and include specific architectural metrics like TDP, memory bandwidth, and interconnect speeds.'
Why this is correct
This approach provides clear negative constraints (exclude marketing) and positive constraints (include specific metrics). By defining the required output format and content, the model is compelled to ignore its tendency to generate generic, flowery text and focus on the hard data points that define the technical architecture.
- ✗
Ask the model to 'Write a shorter summary' in the user prompt.
Why it's wrong here
Asking for a shorter summary does not address the underlying issue of content quality. The model might just produce a shorter version of the same marketing-heavy content. It fails to provide the necessary guidance on prioritizing technical details, which is the root cause of the current undesirable output quality.
- ✗
Decrease the temperature to 0.0 to make the model more factual.
Why it's wrong here
While a lower temperature increases consistency, it does not instruct the model on content prioritization. The model may still default to marketing fluff if that is what it learned as a 'standard' summary style during its training. You must explicitly steer the content via the system prompt instructions.
- ✗
Use few-shot prompting with generic summaries.
Why it's wrong here
Using generic summaries as examples will reinforce the model's tendency to produce marketing-heavy text. To change the output style, you need to provide few-shot examples that demonstrate the exact level of technical depth and professional tone you expect, otherwise, you are just reinforcing the existing bad habit.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
This NCP-GENL practice question is part of Courseiva's free NVIDIA 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 NCP-GENL exam.