CCAO-F Claude Model Fundamentals Practice Question
A support team wants Claude to answer customer questions using only the company's internal help articles. They plan to paste the relevant article text into the prompt before the user's question. Which prompting technique does this describe?
⚠ Common exam trap
The trap here is conflating any prompt that includes extra text with few-shot prompting, when the key distinction is whether the added text is reference material (RAG) or solved examples (few-shot).
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
✓
Retrieval-augmented generation (RAG)
Inserting relevant source documents into the prompt so the model answers from them is retrieval-augmented generation. The retrieval step supplies factual context, and the generation step produces an answer grounded in that context. This differs from zero-shot, few-shot, and chain-of-thought, which address examples, demonstrations, and reasoning traces respectively.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Zero-shot prompting
Why it's wrong here
Zero-shot prompting means asking the model to perform a task without providing examples or reference material. In this scenario the team supplies help-article text, which is additional context beyond the bare question. Therefore it is not zero-shot; the presence of retrieved content moves it into a grounded or retrieval-augmented pattern.
- ✓
Retrieval-augmented generation (RAG)
Why this is correct
RAG combines a retrieval step that fetches relevant documents with generation, where the model answers using that fetched context. Pasting internal help articles before the user question is exactly this pattern: external knowledge is injected into the prompt to ground the response. It reduces hallucination by anchoring answers in provided source material.
- ✗
Chain-of-thought prompting
Why it's wrong here
Chain-of-thought prompting asks the model to reason step by step before giving a final answer. This scenario does not request intermediate reasoning; it supplies source documents to constrain the answer. While reasoning could be added, the defining characteristic here is grounding in retrieved text, not explicit step-by-step deliberation.
- ✗
Few-shot prompting
Why it's wrong here
Few-shot prompting involves including several input-output examples to demonstrate the desired pattern. Here the team inserts reference documents, not solved examples of question-answer pairs. The goal is grounding in source facts rather than teaching a format through demonstrations, so few-shot is the wrong label.
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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 Anthropic exam blueprint
This CCAO-F practice question is part of Courseiva's free Anthropic 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 CCAO-F exam.