Practice resources

Three PM decisions to practise this week

A seven-day Product Mastery practice plan: prioritise a sprint, choose a value metric and map launch stakeholders. About 35 minutes plus feedback.

Practise with feedback

A small plan you can finish

Set aside three short sessions. Make a decision, read the feedback and write down one change you would make. The goal is to practise explaining your reasoning under constraints, not to memorise a preferred answer.

This is a self-paced plan inside Product Mastery. The suggested days are not deadlines. An account is required for the exercises and personalised AI feedback; the resources below are open to read.

Day 1 — make a trade-off

Sprint Planning Prioritization · case study · about 15 minutes. Decide what fits in a sprint when value, effort and dependencies compete. State what you will postpone and what new evidence would change your choice.

Day 3 — choose a value metric

Identifying Value Metrics from Usage Data · data analysis · about 10 minutes. Distinguish activity from evidence that users receive value. Explain the denominator, time window and one guardrail.

Day 7 — bring stakeholders with you

Mapping Stakeholders for a Product Launch · framework exercise · about 10 minutes. Identify who can affect the launch, what they need to know and which disagreement must be resolved first.

What it costs

The Free plan includes five exercise attempts and five AI reviews per month. These three exercises use that same allowance; this plan does not grant extra credits. Other practice or repeat attempts can use the remaining allowance. Existing learners with fewer credits can spread the plan across their reset date or choose a paid plan.

No card is required to start on Free. This plan does not subscribe you to reminders. If you want reminders, choose them in your profile. Suggested timings exclude the time you spend reading and acting on feedback.

How to tell whether it helped

After the third session, read your three notes together. Can you now name the user, the constraint, the trade-off and the evidence behind each decision? Choose one idea to try at work without copying confidential workplace data into an exercise.

AI feedback is a practice aid and can be wrong. Challenge a score when your evidence supports a different conclusion. This is not a hiring assessment or a promise of a job outcome.