Product Discovery Course

Set up the habits, roles, rules, and rhythms that make discovery continuous. This module teaches what discovery is, how to run it every week with a small team, how to keep it ethical and privacy-safe, and how to aim it at outcomes. Lessons are practical, tool-agnostic, and designed to avoid overlap with recruiting, repositories, governance, or collaboration deep-dives covered in later modules.

Build a repeatable system to find, screen, schedule, and maintain the right participants every week. You will learn how to define segments, choose channels, write screeners, set incentives, manage a panel, and pick simple sampling approaches so discovery never stalls.

Pick the right research method for the question. Learn how to run interviews, surveys, product data checks, quick prototypes, diary studies, and usability tests. See strengths and limits of each, and how to combine methods without heavy process.

Build a clean insight pipeline from capture to synthesis, then store findings in a simple, searchable repository. Keep methods light, evidence grounded, and use AI for speed where it helps. No heavy frameworks, just practices your team can repeat every week.

Turn raw insights into a clear map of opportunities that tie to outcomes. Learn simple ways to frame problems, group them, size them, and choose the right mapping method for your context. Keep it lightweight, living, and evidence-linked.

Identify what must be true for your idea to succeed, map those assumptions by importance and evidence, then run the smallest tests that can break the risky ones first. You will use a simple 2x2 assumption map, learn falsification thinking, and build a short risk plan that feeds your next steps. This module sets you up for later work on bets and experiments without going deep into experimentation math.

Turn solid insights into clear product bets. You'll learn how to write a short opportunity brief, frame falsifiable hypotheses, set success and guardrail metrics, and define scope, owners, and decision rules. This is the bridge from discovery to testing, practical, light, and evidence-first.

Make discovery a team sport. Set up simple rituals with design, engineering, and stakeholders so learning turns into decisions. Use clear readouts, short demos, and a decision log. Keep it lightweight, repeatable, and tied to outcomes, not theater.

Put light structure around discovery so teams make better decisions without red tape. This module covers evidence thresholds, a simple definition of done for discovery, a few habit KPIs (like research velocity), knowledge management, and org practices that keep learning ethical and useful. It follows your outline on evidence thresholds, research velocity, and knowledge management as org-level topics.