opportunity-solution-tree

opportunity-solution-tree helps a product team build an Opportunity Solution Tree (OST), a visual framework from Teresa Torres' Continuous Discovery Habits for structuring product discovery. It solves a common failure mode — teams jumping straight to solutions — by forcing them to first map the opportunity space, connecting a single desired outcome to customer opportunities, candidate solutions, and experiments that validate them.

The skill structures the tree across four levels: a measurable desired outcome at the top (a single metric drawn from OKRs or strategy), customer opportunities framed as needs and pains rather than features, multiple solutions per opportunity generated by the Product Trio of PM, Designer, and Engineer, and fast, cheap experiments at the bottom to test assumptions across value, usability, viability, and feasibility risks. It prioritizes opportunities using the Opportunity Score, Importance × (1 − Satisfaction), and enforces key principles: focus on one outcome at a time, prioritize problems over features, generate at least three solutions before choosing to avoid the first-idea trap, loop back when experiments fail, and update the tree continuously as new learning arrives. Its process walks from defining and confirming the outcome, through mapping and prioritizing 3–7 opportunities, generating solutions, and designing 1–2 experiments per promising solution (each with a hypothesis, method, metric, and success threshold), to visualizing the full tree in a hierarchical format and optionally saving it as markdown.

The skill targets product managers, designers, and engineers doing continuous discovery who need to organize research into a coherent, prioritized map of what to build next. It works best when a desired outcome and customer research (interviews, surveys, analytics, feedback) are available, and it can also organize existing opportunities or solution ideas.