Purpose
Use this lesson to compare options against weighted criteria without hiding judgment. The aim is to produce work that a colleague can review and act on, not merely text that sounds convincing.
Lesson Explanation
Scenario: Choose between three help-desk platforms.
Better instruction: Build a decision matrix using cost, integration, security, ease of use, and support. Ask me for weights before scoring; show the score calculation and any assumptions.
A decision matrix makes trade-offs visible, but it does not create objective truth. Define criteria, weights, scoring scale, evidence source, and sensitivity checks. The model should not invent weights or vendor facts. Weights are requested, scoring is visible, and assumptions are stated.
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 “Decision Matrices That Clarify Trade-Offs”?
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compare options against weighted criteria without hiding judgment.
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Why is this request incomplete: Choose between three help-desk platforms.
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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: Build a decision matrix using cost, integration, security, ease of use, and support. Ask me for weights before scoring; show the score calculation and any assumptions.
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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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A decision matrix makes trade-offs visible, but it does not create objective truth. Define criteria, weights, scoring scale, evidence source, and sensitivity checks. The model should not invent weights or vendor facts.
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What would count as an acceptable result here?
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Weights are requested, scoring is visible, and assumptions are stated.
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Name one detail you would verify before using an AI result for “Decision Matrices That Clarify Trade-Offs”.
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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 “Decision Matrices That Clarify Trade-Offs” 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 “Decision Matrices That Clarify Trade-Offs”?
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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
Build a decision matrix using cost, integration, security, ease of use, and support. Ask me for weights before scoring; show the score calculation and any assumptions.