Intermediate · 6 modules · 18 lessons

Product Thinking

Explore Product Thinking through 6 modules and 18 approachable lessons, with examples, practice, feedback, and a final hands-on project.

Written and edited by . Updated 2026-08-24.

What you will learn

  • Frame the user problem before selecting an AI solution.
  • Assess feasibility, product value, experience, and risk together.
  • Define experiments and decision rules for responsible product delivery.

Course outline

Module 01

Start with the Problem, Not the Hype

Begin with the user, the job they need to complete, the evidence, and the outcome they need.

  1. Problem Space · 12 minutes
  2. Users and Jobs · 16 minutes
  3. Outcomes · 20 minutes

Practice output: Problem statement

Module 02

Opportunity and Value

Map opportunities by how often a problem occurs, how severe it is, and what value a solution could create.

  1. Opportunity Mapping · 12 minutes
  2. Frequency and Severity · 16 minutes
  3. Value Exchange · 20 minutes

Practice output: Opportunity solution tree

Module 03

Assessing AI Feasibility

Check data readiness, model capability, uncertainty, and the choice to build or use an existing service.

  1. Data Readiness · 12 minutes
  2. Model Capability · 16 minutes
  3. Build or Buy · 20 minutes

Practice output: AI feasibility canvas

Module 04

Designing the AI Experience

Help users understand how AI works, how confident the result is, how to correct it, and what happens when it fails.

  1. Mental Models · 12 minutes
  2. Confidence and Feedback · 16 minutes
  3. Human Override · 20 minutes

Practice output: AI experience flow

Module 06

Strategy, Roadmap, and Product Brief

Bring choices, rollout plans, stakeholder needs, and work sequence into one clear story.

  1. Strategic Choices · 12 minutes
  2. Rollout and Roadmap · 16 minutes
  3. AI Product Brief · 20 minutes

Practice output: AI product brief