Purpose
Use this lesson to draft formulas and explanations while verifying them in the actual spreadsheet. The aim is to produce work that a colleague can review and act on, not merely text that sounds convincing.
Lesson Explanation
Scenario: Calculate a 10% discount only when column C says Approved.
Better instruction: Suggest an Excel formula that applies a 10% discount to B2 when C2 equals “Approved”; explain how to test it with one approved and one unapproved row.
AI can propose formulas, but it does not see your workbook unless you provide the structure. Name cell references, the expected behavior, and test cases. Run the formula in the spreadsheet and check edge cases such as blanks. The formula behaves differently for Approved and unapproved rows and is tested in the workbook.
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 “Using AI Around Spreadsheet Formulas”?
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draft formulas and explanations while verifying them in the actual spreadsheet.
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Why is this request incomplete: Calculate a 10% discount only when column C says Approved.
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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: Suggest an Excel formula that applies a 10% discount to B2 when C2 equals “Approved”; explain how to test it with one approved and one unapproved row.
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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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AI can propose formulas, but it does not see your workbook unless you provide the structure. Name cell references, the expected behavior, and test cases. Run the formula in the spreadsheet and check edge cases such as blanks.
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What would count as an acceptable result here?
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The formula behaves differently for Approved and unapproved rows and is tested in the workbook.
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Name one detail you would verify before using an AI result for “Using AI Around Spreadsheet Formulas”.
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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 “Using AI Around Spreadsheet Formulas” 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 “Using AI Around Spreadsheet Formulas”?
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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
Suggest an Excel formula that applies a 10% discount to B2 when C2 equals “Approved”; explain how to test it with one approved and one unapproved row.