Worked case: teacher exploring three AI role families

Suppose the team begins with four available hours per week, classroom teaching experience, spreadsheet skill, interests, and current role descriptions. They label these inputs as approved and mark every missing field [UNKNOWN]. Their first request is: “Use only the approved material. Return a structured draft and list questions that could change the result.” It produces something useful, but one decision lacks support.

Instead of accepting the polished draft, the reviewer compares it with five current job descriptions, a practitioner conversation, a finished artifact, and a candid energy log. They correct the unsupported portion, repeat the bounded request, and document why the second version passes. The worked case shows the important habit: improve the evidence trail, not just the wording. If the review reveals a recommendation is based on a stereotype, a salary claim has no current source, or the experiment requires sharing student records, the proper result is escalation, not a workaround.

Write a short record before you move on. For a teacher with four hours each week choosing two-week career experiments, state the claim or choice under review, then name the evidence that supports it: five current job descriptions, a practitioner conversation, a finished artifact, and a candid energy log. 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. An educator exploring adjacent ai work without taking a career break 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 recommendation is based on a stereotype, a salary claim has no current source, or the experiment requires sharing student records. A documented pause is a successful outcome when it keeps a weak result from becoming a consequential one.