Purpose
Use this lesson to combine prompt design, testing, and review into one deliverable. The aim is to produce work that a colleague can review and act on, not merely text that sounds convincing.
Lesson Explanation
Scenario: Build a system that turns weekly team notes into an executive update.
Better instruction: Design the prompt system: input fields, transformation steps, output format, quality rubric, test cases, and human approval step. Include one sample input and expected output outline.
A professional prompt system is more than one clever message. It has defined inputs, reusable instructions, an output shape, tests for failure cases, and a human approval route. The capstone proves that you can make AI work repeatably for a real business process. The system includes inputs, steps, output format, rubric, tests, approval, and a sample case.
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 “Capstone: Build a Work-Ready Prompt System”?
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combine prompt design, testing, and review into one deliverable.
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Why is this request incomplete: Build a system that turns weekly team notes into an executive update.
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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: Design the prompt system: input fields, transformation steps, output format, quality rubric, test cases, and human approval step. Include one sample input and expected output outline.
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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 professional prompt system is more than one clever message. It has defined inputs, reusable instructions, an output shape, tests for failure cases, and a human approval route. The capstone proves that you can make AI work repeatably for a real business process.
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What would count as an acceptable result here?
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The system includes inputs, steps, output format, rubric, tests, approval, and a sample case.
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Name one detail you would verify before using an AI result for “Capstone: Build a Work-Ready Prompt System”.
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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 “Capstone: Build a Work-Ready Prompt System” 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 “Capstone: Build a Work-Ready Prompt System”?
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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
Design the prompt system: input fields, transformation steps, output format, quality rubric, test cases, and human approval step. Include one sample input and expected output outline.