Mastery: your playbook

Your mastery artifact is a career experiment portfolio with job-description matrix, skill evidence map, project, practitioner notes, and next-decision memo. It should let a competent colleague repeat choose and run a two-week AI career experiment instead of guessing a forever title without inheriting unstated assumptions. Include the job card, source requirements, prompt contract, examples, rubric, privacy boundary, escalation rule, and recovery steps.

Use inventory → scan roles → choose experiment → build → interview → decide as the spine. For every stage, name the input, action, output, owner, check, and stop condition. Include the concrete prompt:

I enjoy explaining hard ideas, interviewing people, and editing. Skills: classroom teaching, spreadsheets, basic research. Constraint: four hours weekly and no career break. Suggest three role-family experiments. For each: transferable evidence, one gap, a two-week portfolio artifact, and one professional to learn from. Do not predict salary or hiring probability without current sources.

Then include a specimen response: Three bounded experiments across AI education, product operations, and evaluation, each producing evidence rather than promising a job outcome. Label it as an example, not a guaranteed result. Attach proof from the independent check: you must collect five current job descriptions per path, count repeated requirements, interview a practitioner, inspect current labor sources, and evaluate whether the work itself fits.

Run the same playbook on a second case that differs in one meaningful way. Keep the quality bar fixed. Explain which context fields and constraints changed. If the workflow only succeeds on the memorized example, it is not mastered.

Teach the method in five minutes to someone who has not read this chapter. Ask them to identify the source of truth, the riskiest failure, and the human decision. Their answers reveal whether your playbook is explicit.

Score yourself:

1. Framing: I can reject work outside the stated job.
2. Context: I distinguish evidence, assumptions, and untrusted input.
3. Prompting: I constrain output and request inspectable artifacts.
4. Verification: I use an external check, not model confidence.
5. Safety: I enforce this boundary: remove employer-confidential examples, student data, contact details, and sensitive employment history before sharing career materials.
6. Operations: I can recover from chasing trendy titles; fabricated salary claims; treating course completion as evidence; ignoring domain expertise; building projects no target role values.
7. Communication: I disclose limitations and ownership clearly.

A weak score is a practice target, not a reason to pad the playbook. Titles change faster than durable work. Optimize for evidence that you can perform a useful task, explain trade-offs, and learn from feedback.

Package the project as run one two-week role experiment and publish a concise case study showing problem, process, judgment, and learning. Show the before state, constraint decisions, failed case, correction, measured result, and reflection. Remove sensitive inputs and avoid claiming impact you did not measure. Professional credibility comes from showing judgment under constraints.