Auditable Reasoning Prompts
Make the laptop pick auditable without hidden thoughts
This page advances one continuous project: a college buyer comparing three laptops under price, battery, weight, and required-software constraints.
1Try it yourself
Interactive slate
ReasoningSteps
This playground is next on the build list. Read the idea below, then continue along the spine — Lane A starts fully interactive from the first lesson.
2Learn the idea
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Define the job at the right size
The job is not “use AI.” It is to create a comparison plan, an evidence table, and a short recommendation with explicit unknowns for a student who needs to verify seller claims before spending money. That wording makes the audience, deliverable, and accountable decision visible. A model can help draft, sort, transform, or compare. It cannot quietly decide that the work is accurate, safe, approved, or ready to release. Name the owner who accepts the result and the person who can stop it.
The authoritative inputs are the budget, measured battery tests, weight, required software, warranty terms, and seller URLs. If any is absent, label it unknown instead of letting a plausible answer fill the gap. The job is complete only when the artifact serves its intended person, each important claim or choice can be checked, and a human owner has reviewed the consequence.
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A decision record for this scenario
Write a short record before you move on. For a college buyer comparing three laptops under price, battery, weight, and required-software constraints, state the claim or choice under review, then name the evidence that supports it: manufacturer specifications, an independent battery test, a software compatibility page, and the buyer's budget. Next, name what the evidence does not establish. This last line prevents a narrow test from becoming a broad promise. If another team member opened your record next month, they should be able to reproduce the review without trusting your memory.
Now make the trade-off visible. A student who needs to verify seller claims before spending money may value speed, clarity, cost, control, or reassurance differently. Explain which of those mattered in the current version and why. Do not let a model choose the trade-off simply because it can produce a confident answer. The responsible owner decides whether the upside justifies the remaining uncertainty.
Finally, connect the decision to a next action. If the current evidence is enough, identify the smallest safe step forward. If it is not, request a specific source, approval, or test. The stop condition remains concrete: a deciding cell lacks a source, a specification conflicts across sources, or software compatibility has not been checked. A documented pause is a successful outcome when it keeps a weak result from becoming a consequential one.
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Before you start
Why this matters
Picture the moment before you begin work on a college buyer comparing three laptops under price, battery, weight, and required-software constraints. The person depending on it is a student who needs to verify seller claims before spending money. Write down one fact that must remain exact, one choice a person—not a model—must make, and one condition that would make you pause. Your three notes are a better starting point than a broad request for “something good.” In this topic, the result is a comparison plan, an evidence table, and a short recommendation with explicit unknowns; it earns trust only when another person can see how it was made and where its limits are.
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