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Opportunity Solution Tree

Pawel HurynCommunityCreated by Pawel Huryn

  • Skill
  • Workflow
  • Business and productivity
  • MIT
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From the author

Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when structuring discovery work, mapping opportunities to solutions, or deciding what to build next.
— the description by Pawel Huryn

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Opportunity Solution Tree (OST) is a visual product discovery framework that helps teams avoid the trap of jumping straight to features. By connecting a single desired business outcome to customer needs, potential solutions, and validation experiments, it ensures that development efforts are grounded in real user problems. This skill guides teams through the process of defining outcomes, identifying and prioritizing customer opportunities, brainstorming multiple solutions, and designing experiments to test assumptions.

What it does

  • Defines a clear, measurable business outcome as the foundation for discovery.
  • Maps customer pain points and needs as opportunities rather than features.
  • Facilitates the generation of multiple solutions for every identified opportunity.
  • Designs fast, low-cost experiments to validate solution assumptions.
  • Prioritizes opportunities using data-driven scoring methods.
  • Visualizes the entire discovery hierarchy for team alignment.

When to use it

  • When starting a new product discovery cycle.
  • When a team is struggling to connect their roadmap to business outcomes.
  • When you need to prioritize which customer problems to solve next.
  • When you want to avoid the bias of committing to the first solution idea.
  • When conducting continuous discovery based on ongoing user research.

Advantages

  • Prevents premature solution commitment.
  • Ensures alignment between business goals and customer needs.
  • Encourages collaborative ideation across the product trio.
  • Reduces risk through iterative, evidence-based validation.
  • Provides a clear, living map of the product discovery process.

Usage examples

“Help me build an OST for increasing our mobile app's 7-day retention rate.”
The agent will guide you to define the outcome, extract opportunities from your user research, brainstorm solutions, and design experiments to test them.
“I have a list of customer complaints about our checkout process. How do I turn these into an Opportunity Solution Tree?”
The agent will help you frame those complaints as customer opportunities, prioritize them, and map them to potential solutions and validation tests.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/phuryn/opportunity-solution-tree/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip opportunity-solution-tree.zip -d .agents/skills

Documentation by Pawel Huryn

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):

  1. 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.

  2. 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.

  3. 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."

  4. 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

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

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

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

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

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

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

Think step by step. Save as markdown if substantial.

Further Reading

Files

SKILL.md

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):

  1. 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.

  2. 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.

  3. 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."

  4. 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

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

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

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

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

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

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

Think step by step. Save as markdown if substantial.

Further Reading

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

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Attribution and licence

Created by
Pawel Huryn
Publisher
Pawel Huryn (Community)
Source
phuryn/pm-skills · pm-product-discovery/skills/opportunity-solution-tree · commit 2a12295
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Pawel Huryn or Pawel Huryn.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download opportunity-solution-tree.zip