Careers in AI
Ask for experiments with portfolio evidence, not vibes
This page advances one continuous project: a teacher with four hours each week choosing two-week career experiments.
1Learn the idea
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Make the request produce reviewable evidence
Use a request that asks for intermediate work you can inspect: generate three role-family experiments with a two-week artifact, one interview question, a skill gap, and no hiring prediction. A useful prompt says what the tool may use, the required format, and what it should do when evidence is missing. It does not demand secret internal reasoning or reward confident guessing.
Try a two-pass loop. First ask for the structured artifact and questions. Then correct one concrete problem using the original evidence. This preserves the distinction between the source and the instruction. If the result contains a claim you cannot trace, ask it to mark the claim unsupported rather than rewrite it more smoothly.
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A decision record for this scenario
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.
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Why this matters
Picture the moment before you begin work on a teacher with four hours each week choosing two-week career experiments. The person depending on it is an educator exploring adjacent AI work without taking a career break. 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 three small experiments, reflections, and a portfolio note rather than a prediction about a permanent title; it earns trust only when another person can see how it was made and where its limits are.
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