product-discovery

# Product Discovery

Run structured discovery to identify high-value opportunities and de-risk product bets.

## When To Use

Use this skill for:
- Opportunity Solution Tree facilitation
- Assumption mapping and test planning
- Problem validation interviews and evidence synthesis
- Solution validation with prototypes/experiments
- Discovery sprint planning and outputs

## Core Discovery Workflow

1. Define desired outcome
- Set one measurable outcome to improve.
- Establish baseline and target horizon.

2. Build Opportunity Solution Tree (OST)
- Outcome -> opportunities -> solution ideas -> experiments
- Keep opportunities grounded in user evidence, not internal opinions.

3. Map assumptions
- Identify desirability, viability, feasibility, and usability assumptions.
- Score assumptions by risk and certainty.

Use:
```bash
python3 scripts/assumption_mapper.py assumptions.csv
```

4. Validate the problem
- Conduct interviews and behavior analysis.
- Confirm frequency, severity, and willingness to solve.
- Reject weak opportunities early.

5. Validate the solution
- Prototype before building.
- Run concept, usability, and value tests.
- Measure behavior, not only stated preference.

6. Plan discovery sprint
- 1-2 week cycle with explicit hypotheses
- Daily evidence reviews
- End with decision: proceed, pivot, or stop

## Opportunity Solution Tree (Teresa Torres)

Structure:
- Outcome: metric you want to move
- Opportunities: unmet customer needs/pains
- Solutions: candidate interventions
- Experiments: fastest learning actions

Quality checks:
- At least 3 distinct opportunities before converging.
- At least 2 experiments per top opportunity.
- Tie every branch to evidence source.

## Assumption Mapping

Assumption categories:
- Desirability: users want this
- Viability: business value exists
- Feasibility: team can build/operate it
- Usability: users can successfully use it

Prioritization rule:
- High risk + low certainty assumptions are tested first.

## Problem Val...