Purpose
Use this lesson to improve a result through deliberate versions and tests. The aim is to produce work that a colleague can review and act on, not merely text that sounds convincing.
Lesson Explanation
Scenario: A first draft of a training outline is too advanced for new hires.
Better instruction: Revise version 1 for new hires: define technical terms, add one worked example per section, and limit each module to 20 minutes. Compare version 2 against those three changes.
Iteration is not random regeneration. Keep the original goal, name the observed defect, change only the relevant instruction, and compare versions using defined tests. This preserves learning about what improved the result. Version 2 addresses terminology, examples, and 20-minute modules, with a comparison.
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 “Iterative Prompt Workflows”?
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improve a result through deliberate versions and tests.
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Why is this request incomplete: A first draft of a training outline is too advanced for new hires.
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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: Revise version 1 for new hires: define technical terms, add one worked example per section, and limit each module to 20 minutes. Compare version 2 against those three changes.
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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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Iteration is not random regeneration. Keep the original goal, name the observed defect, change only the relevant instruction, and compare versions using defined tests. This preserves learning about what improved the result.
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What would count as an acceptable result here?
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Version 2 addresses terminology, examples, and 20-minute modules, with a comparison.
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Name one detail you would verify before using an AI result for “Iterative Prompt Workflows”.
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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 “Iterative Prompt Workflows” 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 “Iterative Prompt Workflows”?
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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.
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Revise version 1 for new hires: define technical terms, add one worked example per section, and limit each module to 20 minutes. Compare version 2 against those three changes.