Purpose
Use this lesson to diagnose a bad result by locating the missing instruction. The aim is to produce work that a colleague can review and act on, not merely text that sounds convincing.
Lesson Explanation
Scenario: The AI wrote a long blog post when you wanted a short LinkedIn post.
Better instruction: Rewrite the instruction: produce one LinkedIn post for operations leaders, 90–120 words, with one practical takeaway and no hashtags.
Do not endlessly regenerate the same vague prompt. Compare the output with the intended result, identify the absent instruction—audience, length, format, source, or boundary—and change that element. Keep a record of the version that works. The revised post is for operations leaders, 90–120 words, practical, and contains no hashtags.
Work in a short cycle: provide the relevant input, state the result and limits, inspect the draft against the acceptance criteria, then revise the instruction when a requirement is missing. Keep the final human decision with the person responsible for the work.
Practice Questions
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What is the main work outcome in “Debugging a Weak Prompt”?
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diagnose a bad result by locating the missing instruction.
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Why is this request incomplete: The AI wrote a long blog post when you wanted a short LinkedIn post.
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It leaves important decisions to guesswork. The lesson shows how to supply the missing purpose, context, boundary, or format.
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Which instruction makes the request operational: Rewrite the instruction: produce one LinkedIn post for operations leaders, 90–120 words, with one practical takeaway and no hashtags.
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It defines a concrete result that can be checked instead of asking for a vague response.
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What principle should guide your prompt for this lesson?
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Do not endlessly regenerate the same vague prompt. Compare the output with the intended result, identify the absent instruction—audience, length, format, source, or boundary—and change that element. Keep a record of the version that works.
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What would count as an acceptable result here?
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The revised post is for operations leaders, 90–120 words, practical, and contains no hashtags.
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Name one detail you would verify before using an AI result for “Debugging a Weak Prompt”.
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Verify the source facts, inputs, numbers, names, dates, policy limits, or assumptions that affect the real decision.
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What should you add if the result is polished but not usable for the scenario in this lesson?
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Add the missing acceptance criteria or output structure, then regenerate and compare against the stated requirement.
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Which is safer: asking for a general answer or stating the business context in this lesson? Why?
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State the business context because it reduces irrelevant guesses and lets the AI tailor the work to the actual situation.
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How would you test the output from “Debugging a Weak Prompt” before sharing it?
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Check it against the requested facts, format, limits, and acceptance criteria; then have the appropriate human reviewer approve it.
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What should the AI do when a required fact is missing in this scenario?
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Flag the missing fact or ask a focused question rather than silently inventing an answer.
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What risk does the lesson warn about for “Debugging a Weak Prompt”?
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Treating fluent output as automatically correct, complete, approved, or fit for real-world use.
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Write the shortest useful improvement to the weak request in this lesson.
View Answer
Rewrite the instruction: produce one LinkedIn post for operations leaders, 90–120 words, with one practical takeaway and no hashtags.