Which Prompt Technique Asks the Model to Show Its Work Step by Step?
Short answer
A Chain-of-thought prompting
Question
Key Takeaways
The test checks your ability to identify chain-of-thought prompting by its signature request for step-by-step reasoning; the trap is confusing it with few-shot prompting, which uses examples.
Learn how asking an Amazon Titan model on Bedrock to 'show its work' exemplifies chain-of-thought prompting, a key technique for numerical reasoning. Community consensus strongly confirms option A.
Common mistake: Choosing C. Few-shot prompting, because the phrase 'show its work' might sound like providing an example, but it actually asks for intermediate reasoning steps, not examples in the prompt.
Expert Analysis
Why the Answer Is Correct
Chain-of-thought (CoT) prompting explicitly instructs the model to produce intermediate reasoning steps before the final answer. The phrase "show its work by explaining its reasoning step by step" is a textbook example of CoT. This technique is well-suited for numerical reasoning challenges because it encourages the model to break down the problem logically. Community comment [2] directly states that this approach "encourages the model to reason through a problem step by step," confirming the correct option.
Why the Other Options Are Wrong
Prompt injection (B) is a security exploit where malicious instructions are inserted into a prompt, not a benign reasoning technique. Few-shot prompting (C) involves providing labeled examples in the prompt, not asking for step-by-step reasoning. Prompt templating (D) refers to reusing parameterized prompt structures, not the explicit instruction to explain reasoning. The description in the question matches none of these other techniques.
Community Comment Notes
All community votes (100%) selected A, showing unanimous consensus. Comments [3] and [4] add valuable context: CoT prompts structure the model's output as a series of logical intermediate steps, improving multi-step problem-solving. Comment [1] simply reinforces the answer with "step by step." These insights align with the official AWS documentation on prompt engineering.
Official Reference
https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-engineering-guidelines.html
This link opens the official vendor documentation in a new tab.
Exam Strategy
Remember that chain-of-thought prompting is identified by explicit requests for step-by-step reasoning, such as "show your work" or "think step by step." Focus on the purpose of the prompt: whether it adds examples (few-shot) or asks for reasoning steps (chain-of-thought).
Community Votes
100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.
Discussion 4 contributions
Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.
From public community threads 4
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kopper2019 👍 2 Answered AA. Chain-of-thought prompting step by step
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chris_spencer 👍 1 Answered AChain-of-thought prompting Chain-of-thought prompting improves the reasoning ability of large language models by prompting them to generate a series of intermediate steps that lead to the final answer of a multi-step problem.
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Jessiii 👍 1 Answered AThis technique encourages the model to reason through a problem step by step, which is exactly what the AI practitioner is doing by asking the model to "show its work by explaining its reasoning step by step."
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ajey255 👍 1 Answered ACoT prompting involves structuring prompts so that the LLM breaks down complex problems into a series of logical, intermediate steps, similar to how a human would when thinking through a problem.
Reader comments & corrections
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