Opportunity Solution Tree Agent Skill

Opportunity Solution Tree (OST)

A visual framework for structuring continuous product discovery. Connects a desired outcome to customer opportunities, possible solutions, and experiments to validate them.

Domain Context

The Opportunity Solution Tree (Teresa Torres, *Continuous Discovery Habits*) is the backbone of modern product discovery. It prevents teams from jumping to solutions by forcing them to first map the opportunity space.

Structure (4 levels):

• Desired Outcome (top) — The measurable business or product outcome the team is pursuing. Should be a single, clear metric (e.g., "increase 7-day retention to 40%"). This comes from your OKRs or product strategy.

• Opportunities (second level) — Customer needs, pain points, or desires discovered through research. These are problems worth solving — not features. Frame them from the customer's perspective: "I struggle to..." or "I wish I could..." Prioritize using Opportunity Score: Importance × (1 − Satisfaction) (Dan Olsen, *The Lean Product Playbook*). Normalize Importance and Satisfaction to 0–1.

• Solutions (third level) — Possible ways to address each opportunity. Generate multiple solutions per opportunity — don't commit to the first idea. The Product Trio (PM + Designer + Engineer) should ideate together. "Best ideas often come from engineers."

• Experiments (bottom) — Fast, cheap tests to validate whether a solution actually addresses the opportunity. Use assumption testing (Value, Usability, Viability, Feasibility risks). Prefer experiments with "skin-in-the-game" (Alberto Savoia) over opinion-based validation.

Key principles:

• One outcome at a time. Don't try to solve everything. Focus the tree on a single desired outcome.
• Opportunities, not features. "Never allow customers to design solutions. Prioritize opportunities (problems), not features."
• Compare and contrast. Always generate at least 3 solutions per opportunity before choosing. Avoid the "first idea" trap.
• Discovery is not linear. Loop back if experiments fail. Kill solutions that don't validate. Explore new branches.
• Continuous, not periodic. Update the tree weekly as you learn from interviews, analytics, and experiments.

Instructions

You are helping a product team build an Opportunity Solution Tree for $ARGUMENTS.

Input Requirements

• A desired outcome or business metric to improve
• Customer research data (interviews, surveys, analytics, feedback)
• Optionally: existing opportunities or solution ideas to organize

Process

• Define the desired outcome — Confirm or help articulate a single, measurable outcome at the top of the tree.

• Map opportunities — From provided research, identify 3-7 customer opportunities (needs/pains). Group related opportunities. Frame each from the customer's perspective.

• Prioritize opportunities — Use Opportunity Score or qualitative assessment to rank. Focus on the top 2-3.

• Generate solutions — For each prioritized opportunity, brainstorm 3+ solutions from PM, Designer, and Engineer perspectives.

• Design experiments — For the most promising solutions, suggest 1-2 fast experiments. Specify: hypothesis, method, metric, success threshold.

• Visualize the tree — Present the full OST in a clear hierarchical format.

Think step by step. Save as markdown if substantial.

Further Reading

• The Extended Opportunity Solution Tree
• What Is Product Discovery? The Ultimate Guide Step-by-Step
• Product Trio: Beyond the Obvious
• Continuous Product Discovery Masterclass (CPDM) (video course)