AI Learning Paths

Paths range from 3 to 5 hours. Each path lists its estimated time upfront, and individual steps show time estimates so you can learn in short sessions. Most people complete a path over 1-2 weeks.

Some paths have prerequisites — for example, "Building AI Features" builds on "AI PM Fundamentals." But paths like "AI Case Studies Deep Dive" and "Prompt Engineering for Product Teams" have no prerequisites and can be started anytime.

Yes. Your progress is saved in your browser's local storage. You can close the page, come back later, and pick up where you left off. Progress is per-device — it won't sync across different browsers or devices.

The learning paths themselves are free. Some linked content (marked as PRO) requires a subscription to access, but the majority of content in every path is freely available.

Exercise steps give you a hands-on prompt — something to write, build, or analyze. They turn passive reading into active practice. Checkpoint steps ask reflection questions to help you consolidate what you learned. Both are self-directed — you mark them complete when you're satisfied with your work.

If you're a Product Manager new to AI, start with "AI PM Fundamentals." If you're a Designer, start with "AI UX Design Foundations." If you want a quick, standalone experience, try "AI Case Studies Deep Dive" — it has no prerequisites and gives you a broad view of what works in AI products.

Yes. The exercise and checkpoint steps work well for team discussions. Have team members complete a path individually, then meet to compare exercise outputs and discuss checkpoint questions together.

Learning paths are curated sequences with a clear progression. Each path builds knowledge step by step, mixes reading with hands-on practice, includes reflection checkpoints, and tracks your progress. It's structured learning, not browsing.