| name | Continuous Discovery |
| description | Full Continuous Discovery Habits pipeline: create interview snapshots, synthesize patterns, create opportunities, generate solutions, and identify and test assumptions.
|
Continuous Discovery
This skill implements the Continuous Discovery Habits (CDH) methodology by Teresa Torres. It covers the full pipeline from raw interview data to tested assumptions.
Pipeline overview
Individual Interviews -> Create Snapshots -> Synthesize Patterns -> Create Opportunities -> Generate Solutions -> Identify & Test Assumptions
| | | | | |
[Raw Data] [Structured Stories] [Shared Patterns] [Problem Statements] [Product Ideas] [Risks & Tests]
Workflows
Each workflow has a detailed reference document:
-
Create Interview Snapshots - references/create-interview-snapshots.md
Extract structured insights from qualitative interviews or user tests.
-
Synthesize Interview Snapshots - references/synthesize-interview-snapshots.md
Analyze multiple snapshots to identify common patterns and create comprehensive insights.
-
Create Opportunities - references/create-opportunities.md
Extract and prioritize opportunities from snapshots and synthesis using Opportunity Solution Trees.
-
Generate Solutions - references/generate-solutions.md
Generate multiple potential solutions through AI-human collaborative ideation.
-
Identify and Test Assumptions - references/identify-and-test-assumptions.md
Extract assumptions, categorize them, prioritize "leap of faith" assumptions, and design lightweight tests.
1. Create Interview Snapshots
When to use
After conducting a qualitative interview or user test session.
Input
Raw interview notes, transcripts, or recordings.
Output
- Format: Markdown (
.md)
- Location:
user-interviews/snapshots/
- Filename:
snapshot-[participant-name]-[date].md
Process
- Data Validation: Assess completeness and quality of interview data
- Context Extraction: Identify session type, research goals, and participant context
- Story Identification: Extract specific behavioral stories, not generalizations
- Experience Mapping: Create user journey maps for key stories
- Opportunity Analysis: Identify pain points, needs, and improvement areas
- Insight Synthesis: Recognize patterns and behavioral insights
- Snapshot Creation: Compile into structured interview snapshot
- Quality Review: Validate completeness and clarity
For the full output template and guidelines, see references/create-interview-snapshots.md.
2. Synthesize Interview Snapshots
When to use
- After completing 3-5+ interviews on the same topic
- Before creating opportunities or generating solutions
- When sharing research findings with stakeholders
Input
- Minimum 3-5 interview snapshots from step 1
- All snapshots should follow consistent format and cover similar topics
Output
- Format: Markdown (
.md)
- Location:
user-interviews/synthesis/
- Filename:
synthesis-[initiative-name]-v[version].md
Key features
- Incremental synthesis: Process only new snapshots when updating existing synthesis
- Version management: Auto-increment version numbers, never overwrite
- Pattern recognition: Behavioral patterns, emotional journeys, workarounds
For the full framework, see references/synthesize-interview-snapshots.md.
3. Create Opportunities
When to use
- After completing interview snapshots or synthesis
- When identifying customer problems worth solving
Input
- Interview snapshots from
user-interviews/snapshots/
- Synthesis documents from
user-interviews/synthesis/
- Strategic materials from
company-level-context/
Output
- Format: Markdown (
.md)
- Location:
opportunities/[topic]/
- Filename:
opportunities-[topic]-v[version].md
Key principles
- Focus on customer needs, pain points, and desires (not feature requests)
- Use problem-focused statement format: "I want to ~ but ~ makes it difficult"
- Organize using Opportunity Solution Tree structure
- Pause for user review at two checkpoints
For the full process, see references/create-opportunities.md.
4. Generate Solutions
When to use
- After identifying a clear target opportunity
- Before committing to a single solution approach
Input
- Prioritized opportunities with supporting evidence
- Direct opportunity input from user
Output
- Format: Markdown (
.md)
- Location:
solutions/[topic]/
- Filename:
solutions-[topic]-v[version].md
Critical rule
MANDATORY: The user must generate at least 3 individual ideas before the agent generates any solutions. If the user requests solutions without individual ideation, stop and explain the requirement.
Process
- Review target opportunity
- Individual ideation (human) - MANDATORY
- AI-human collaborative ideation
- Repeat and expand (target 15-20 ideas)
- Evaluate and select top 3
For the full process, see references/generate-solutions.md.
5. Identify and Test Assumptions
When to use
- After creating opportunities
- When preparing to generate or downselect solutions
- Whenever a new idea is proposed and you need to surface risks
Input
- Prioritized opportunities
- Early solution sketches
- Interview snapshots and synthesis
Output
- Format: Markdown (
.md)
- Location:
assumptions/[topic]/
- Filename:
assumptions-[opportunity-name]-v[version].md
Key concepts
- Five categories: Desirability, Usability, Feasibility, Viability, Ethical
- Assumption Mapping: 2D grid (Evidence Known x Importance)
- Leap of Faith (LoFA): Maximum 3 assumptions from top-right quadrant (Weak Evidence + More Important)
- Test Cards: Smallest viable simulation with clear success criteria
For the full process, see references/identify-and-test-assumptions.md.
Shared guidelines
File naming
All CDH outputs use semantic naming:
- Use kebab-case topic/initiative names
- Auto-increment version numbers (v1 -> v2 -> v3)
- Never overwrite existing files
- Check for existing files before creating new ones
Quality standards
- Focus on concrete behaviors over opinions or intentions
- Preserve customer language and exact quotes
- Document evidence strength for each insight
- Connect all outputs back to the Opportunity Solution Tree
Follow the writing standards in _shared/writing-standards.md for all outputs.
