CCDV-F Prompt and Context Engineering Practice Question
A developer needs Claude to perform a complex data transformation and then explain its work. To get the best results, what order should these tasks be requested in the prompt?
⚠ Common exam trap
Candidates ask for explanations before transformations, forcing the model to hypothesize steps instead of grounding explanations in actual generated work.
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
✓
Request the transformation first, followed by the explanation of the steps taken.
The order of operations in a prompt significantly affects the model's performance. By asking the model to perform the transformation first and then explain it, you allow the model to use its own generated output as context for the explanation. This ensures the explanation is grounded in the actual work performed, rather than being a hypothetical description.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ask for the explanation first, then the transformation, to set the context.
Why it's wrong here
Asking for the explanation first is often counter-productive because the model has to describe a transformation it hasn't actually performed yet. This can lead to a disconnect where the explanation describes one logic, but the actual transformation follows a different, potentially flawed, path during the subsequent generation.
- ✗
Ask for both simultaneously in a single sentence to ensure they are linked.
Why it's wrong here
Combining two distinct tasks into one instruction can lead to 'task dilution,' where the model fails to follow all parts of the request. Claude performs best when tasks are presented sequentially or in a clear, structured list that allows it to focus on one logical operation at a time.
- ✓
Request the transformation first, followed by the explanation of the steps taken.
Why this is correct
This sequence leverages the model's autoregressive nature. Once the transformation is generated, it becomes part of the local context that the model can 'look back' at when writing the explanation. This leads to much more accurate and faithful descriptions of the work actually performed by the model.
- ✗
Put the explanation in the system prompt and the transformation in the user prompt.
Why it's wrong here
The system prompt is for general rules and personas, not for specific task outputs like an explanation of a particular data point. Mixing these across prompt types would be confusing and would not provide the sequential flow needed for the model to explain a specific transformation accurately.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Anthropic exam blueprint
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