AI Product Management (AIPM) — Live Training

Phase goal: Understand what a PM does, how a business makes money, and research the market and competitors.

• PM role, types of PMs and PM skills (0.5h)
• Business model basics and B2B vs B2C (2.5h)
• Market and competitor research (3h)

PM role, types of PMs and PM skills (0.5h): What a PM owns, and how the role differs from a product owner, project manager and engineer. A short comparison of consumer, B2B, platform, technical, growth and AI PM roles. Core skills: understanding users, business thinking, prioritisation, communication and working with data. This course focuses on a new product, not growth work.

🧩 Claude asset built or adapted in class: PM role and skills prompt file.
✅ Check the output: Check that the comparison describes responsibilities, not fixed job titles or a promise of eligibility for a role.

Business model basics and B2B vs B2C (2.5h): Who uses, who pays, who decides, and how a business makes money. Build a simple business model canvas. Compare buying and selling in B2B and B2C. Learners introduce their capstone idea within this work.

🧩 Claude asset built or adapted in class: Business Model project with reusable instructions and a canvas template.
✅ Check the output: Separate known facts from assumptions, and verify market and revenue claims.

Market and competitor research (3h): Find sources, compare direct competitors and alternatives, identify gaps, and use SWOT as a short summary. Do a manual comparison before using AI.

🧩 Claude asset built or adapted in class: Competitor Research skill and comparison template.
✅ Check the output: Open the sources behind claims, and check dates, competitor facts and unsupported conclusions.

A dedicated session after Discover to clear doubts before moving on.

Phase goal: Work out who the users, customers and buyers are, talk to them properly, and decide whether the problem is worth solving.

• User vs customer vs buyer, and personas (2h)
• User research and the mom test (2h)
• Jobs-to-be-done and user motivation (1h)
• Is the problem worth solving? Finding a starting point (1h)

User vs customer vs buyer, and personas (2h): Identify the person using the product, the paying customer and the buying decision-maker. Build user and buyer personas from evidence and label assumptions.

🧩 Claude asset built or adapted in class: Persona project with evidence notes and a persona template.
✅ Check the output: Compare every claim with interview or research evidence. An AI persona is not a real user.

User research and the mom test (2h): Choose who to interview, write questions about past behaviour rather than opinions, practise interviews and summarise what was said. AI helps prepare and organise research. It does not replace talking to people.

🧩 Claude asset built or adapted in class: Interview Guide skill and research-notes project.
✅ Check the output: Remove leading questions, compare summaries with the original notes and find anything invented.

Jobs-to-be-done and user motivation (1h): Describe the progress a user is trying to make and the situation around it. Use B=MAT briefly to discuss motivation, ability and a prompt for action.

🧩 Claude asset built or adapted in class: Jobs-to-be-done and motivation prompt file.
✅ Check the output: Check that the job follows from evidence and is not a rewritten feature request.

Is the problem worth solving? Finding a starting point (1h): Judge how important and frequent the problem is, what the alternatives are and how willing people are to change. Choose a narrow first group and problem (the wedge). Decide what evidence would change the decision.

🧩 Claude asset built or adapted in class: Problem-check skill or prompt file.
✅ Check the output: Ask for the strongest case against the idea. Challenge assumptions rather than accepting an AI score.

Learners bring their business model, competitor work, personas and research notes for feedback.

Phase goal: Turn research into a small, testable first version with clear requirements and a prototype.

• User journeys (1h)
• Prioritisation (1.5h)
• MVP: a small first version worth testing (1.5h)
• PRD and user stories (2h)
• Design basics and AI prototyping lab (2h)

User journeys (1h): Map the steps users take today, their pain points and the proposed flow. Use the persona and research already prepared.

🧩 Claude asset built or adapted in class: Journey Map prompt and template in the capstone project.
✅ Check the output: Walk through the journey against real examples and check for missing steps.

Prioritisation (1.5h): Use RICE and MoSCoW to discuss priorities and trade-offs. Scores help a conversation. They do not decide what is right.

🧩 Claude asset built or adapted in class: Prioritisation skill and scoring template.
✅ Check the output: Challenge estimates and change one score to see whether the order holds.

MVP: a small first version worth testing (1.5h): Choose the first user, core problem and smallest useful test. Decide what to include, exclude and learn before building more.

🧩 Claude asset built or adapted in class: MVP Scoping project.
✅ Check the output: Check that every included feature supports the first problem or test, and remove extras.

PRD and user stories (2h): Write a product requirements document with the problem, user, scope, flows, requirements, assumptions and success measures. Break it into user stories and acceptance criteria. Use AI to draft and review, while the PM stays responsible for decisions.

🧩 Claude asset built or adapted in class: PRD project and User Story skill.
✅ Check the output: Read as an engineer: find ambiguity, missing edge cases and acceptance criteria that cannot be checked.

Design basics and AI prototyping lab (2h): Draw simple wireframes, discuss clear flows and basic UX, then create and review a prototype with an AI tool. A prototype communicates and tests an idea. It is not a production-ready product.

🧩 Claude asset built or adapted in class: Prototype instructions and review checklist in the capstone project.
✅ Check the output: Inspect the screens and flows against the PRD, and note missing behaviour and what the prototype does not prove.

Learners bring their MVP, PRD and prototype for feedback.

Phase goal: Decide how success is measured, plan the launch and present the full product case.

• Defining metrics (1.5h)
• Go-to-market (1.5h)
• Stakeholder management (1h)
• Capstone walkthrough (1h)

Defining metrics (1.5h): Choose a main success measure (L1) and supporting measures (L2). Compare leading signals with lagging outcomes. Define how each metric is measured and what decision it informs.

🧩 Claude asset built or adapted in class: Metrics skill and measurement template.
✅ Check the output: Check denominators, data availability and whether a measure can be gamed.

Go-to-market (1.5h): Choose the first audience, a one-line value proposition, the first channel, launch activities and a small launch plan. Positioning is a light part of the value proposition, not a separate topic.

🧩 Claude asset built or adapted in class: Go-to-market project and launch-plan template.
✅ Check the output: Check that the audience, channel, message and claims match the research and the MVP.

Stakeholder management (1h): Work with engineering, design, QA and business teams. Explain trade-offs, handle competing requests and practise a short stakeholder update.

🧩 Claude asset built or adapted in class: Stakeholder Update skill.
✅ Check the output: Check that the update makes decisions, open questions and next steps clear, with no invented commitments.

Capstone walkthrough (1h): Show the full product case from problem to launch plan and answer questions. The hour is used for selected walkthroughs and common feedback. Individual feedback comes from the two capstone clinics.

🧩 Claude asset built or adapted in class: Capstone presentation prompt and case-review checklist.
✅ Check the output: Trace claims and decisions back to evidence, and name the remaining assumptions and honest limits.

A final session at the end of the course to clear remaining doubts.