name: continuous-discovery
description: "Guide a PM through continuous discovery using Teresa Torres' Continuous Discovery Habits, Marty Cagan's product discovery, Dual-Track Agile, and Opportunity Solution Trees. Covers weekly interview cadence, experience mapping and interview synthesis, opportunity scoring, atomic research nuggets (Tomer Sharon), research repositories, discovery-to-OKR connection, discovery cadence metrics, Product Trio collaboration, story mapping integration, discovery anti-patterns and failure modes, and outcome-based discovery. Use when running discovery, building an Opportunity Solution Tree, adopting continuous discovery habits, connecting discovery to delivery, or answering PM interview questions about discovery practices."
argument-hint: "[describe the product outcome you are pursuing, your current discovery practices (if any), your team composition, and what aspect of discovery you want to improve]"

Continuous Discovery Guide

Continuous discovery is the ongoing practice of making small research touchpoints with customers each week to inform product decisions. Discovery is not a phase -- it is a weekly cadence embedded in how the team works.

Apply this skill to: $ARGUMENTS

Step 1: Establish the Discovery Mindset

Discovery Is Not a Phase

The Product Trio

Discovery is most effective when three roles collaborate:

All three should attend customer interviews together. When the building team hears directly from customers, shared understanding forms faster and handoff friction drops.

Step 2: The Core Discovery Loop

The continuous discovery cadence runs weekly:

1. Interview at least one customer per week (30-minute sessions)
2. Synthesize insights using Interview Snapshots and Experience Maps
3. Map opportunities on the Opportunity Solution Tree
4. Identify assumptions behind the most promising solutions
5. Design the smallest experiment to test the riskiest assumption
6. Learn and update the OST based on results
7. Repeat

Weekly Interview Cadence

Why weekly matters: Monthly intervals mean the team goes an entire month making decisions without validating assumptions about customer reality. Weekly touchpoints keep teams calibrated.

Recruitment automation: The biggest barrier to continuous interviews is recruiting. Solve this by building an always-on recruitment channel: in-app prompts offering incentives, a standing panel of willing participants, or automated scheduling through CSM introductions.

Step 3: The Opportunity Solution Tree (OST)

The OST is a visual map connecting business outcomes to customer opportunities to solutions to experiments.

Desired Outcome (measurable business goal the team owns)
    |
    Opportunities (unmet user needs, pain points, desires)
        |
        Solutions (product ideas that address a specific opportunity)
            |
            Experiments (tests to validate the solution before building)

Level 1: Desired Outcome

One specific, measurable business outcome the team is responsible for. Not "improve engagement" but "increase weekly active users who complete at least 3 core actions from 34% to 45% by Q3."

Quality test: Can the team influence this outcome through product changes? Is it measurable within the team's sprint cadence?

Level 2: Opportunities

Customer needs, pain points, and desires discovered through interviews. Opportunities are stated in the customer's language, not in product terms.

Well-framed opportunity test: Can you imagine multiple different solutions that would address this opportunity? If only one solution fits, the opportunity is too narrow.

Level 3: Solutions

Multiple solution candidates for each opportunity. One opportunity should have at least 2-3 solutions to enable compare-and-contrast decisions rather than binary go/no-go.

Level 4: Experiments

The smallest, cheapest test to validate the key assumption behind each solution. See the assumption-testing skill for detailed experiment design.

OST Best Practices

• Write the desired outcome before mapping opportunities
• Opportunities must come from validated customer research, not assumptions
• Work on one small opportunity at a time (limit work in progress)
• Treat the OST as a living document that evolves with each interview
• When solutions fail, revisit the opportunity framing, not just the solution approach
• Share the OST visibly with the full team (wall poster, Miro board)

OST Common Mistakes

Step 4: Interview Synthesis

Interview Snapshots (Immediate Synthesis)

After each interview, the Product Trio creates a one-page Interview Snapshot within 15 minutes:

Critical rule: Create snapshots immediately after the interview, not days later. Memory degrades rapidly.

Experience Mapping (Cross-Interview Synthesis)

As patterns emerge across multiple interviews, build Current-State Experience Maps:

1. Map how customers accomplish goals today, step by step
2. Note pain points, workarounds, and emotional highs/lows at each step
3. Identify where multiple interviewees report similar friction
4. These recurring friction points become opportunities on the OST

Atomic Research (Tomer Sharon)

Instead of storing insights in static reports, use atomic research nuggets:

Benefits: Creates a dynamic, searchable research repository. Anyone can create custom playlists of insights by topic. More reusable than slide decks or reports. Continuously updated and accessible across teams.

Synthesis Techniques

Step 5: Opportunity Scoring and Prioritization

Opportunity Scoring Formula

Opportunity Score = Importance + (Importance - Satisfaction)

Prioritization Criteria

When multiple opportunities compete, evaluate:

Rule: Focus on one opportunity at a time. Spreading across multiple opportunities simultaneously dilutes learning velocity.

Step 6: Dual-Track Agile (Discovery + Delivery)

How Two Tracks Work in Parallel

Integration Points

• Discovery feeds validated solutions into the delivery backlog
• Delivery outcomes inform new discovery questions
• Ongoing communication ensures insights directly influence delivery priorities
• The Product Trio bridges both tracks, preventing handoff gaps

Discovery vs. Design Sprints

Step 7: Connecting Discovery to OKRs

Outcome-Based Discovery

Instead of "What do stakeholders want us to build?" ask "What change in user behavior or business metric are we aiming for?"

Learning vs. performance goals: Not all OKRs need to be performance-based. Early in discovery, a valid Key Result is "Identify the top 3 opportunities for reducing churn in the onboarding flow" rather than "Reduce onboarding churn by 15%."

Discovery Cadence Metrics

Track discovery health with these metrics:

Leading indicator of discovery quality: How often a solution is thrown out based on evidence. Teams that never discard ideas are not learning; they are confirming.

Step 8: Story Mapping Integration

Story mapping bridges discovery insights and delivery planning:

1. Assume your solution already exists
2. Map what customers must do to get value from it, step by step
3. Be explicit about who does what and when
4. Identify the thinnest possible slice that delivers the core value (walking skeleton)
5. Update the story map continuously as data arrives from analytics, support, interviews, and experiments

Living document: The story map is not a one-time artifact. As you learn from shipped increments, promote proven bets, reshape work, or drop low-impact ideas.

Step 9: Discovery Anti-Patterns

Step 10: Research Repository (ResearchOps)

Building an Organizational Research Repository

Repository Benefits

• Reduces duplicate research (teams discover what others already learned)
• Enables cross-team pattern recognition
• Creates institutional memory that survives team turnover
• Supports regulatory and compliance documentation of user research

Output Template

CONTINUOUS DISCOVERY PLAN
Product: [Name]
Team: [PM, Designer, Engineer names]
Desired Outcome: [Specific measurable outcome from OKRs]
Timeframe: [When we need to achieve it]
Date: [Today]

CURRENT DISCOVERY STATE
Interview cadence: [Current frequency]
Synthesis method: [How insights are captured today]
Key gap: [What is missing or broken in current discovery practice]

OPPORTUNITY SOLUTION TREE

Desired Outcome: [Metric and target]

Opportunity 1: [Customer-language statement]
  Evidence: [Interview quotes, data points, number of sources]
  Confidence: [High / Medium / Low]
  Solutions:
    Solution A: [Description]
      Riskiest assumption: [Statement]
      Experiment: [Cheapest valid test]
    Solution B: [Description]
      Riskiest assumption: [Statement]
      Experiment: [Cheapest valid test]

Opportunity 2: [Customer-language statement]
  Evidence: [Sources]
  Confidence: [Level]
  Solutions:
    Solution C: [Description]
    Solution D: [Description]

OPPORTUNITY PRIORITIZATION
Focus opportunity: [Which one and why]
Scoring: Importance [X/10], Satisfaction [X/10], Score [X]
Evidence strength: [Number of independent interviews]

DISCOVERY CADENCE PLAN
| Week | Interview Target | Synthesis Activity | Experiment |
|------|-----------------|-------------------|------------|
| W1   | [Who]           | [Snapshot + map]  | [Test]     |
| W2   | [Who]           | [Snapshot + map]  | [Test]     |
| W3   | [Who]           | [Cross-synthesis] | [Test]     |
| W4   | [Who]           | [OST review]      | [Decision] |

RECRUITMENT PLAN
Channel: [How we recruit interviewees]
Incentive: [What we offer]
Scheduling: [Automated or manual]

DISCOVERY HEALTH METRICS
| Metric | Current | Target |
|--------|---------|--------|
| Weekly interview rate | [X] | 1+ per week |
| Assumptions tested/sprint | [X] | 1-2 per sprint |
| OST update frequency | [X] | Weekly |
| Trio participation | [X%] | 80%+ |

ANTI-PATTERN CHECK
[Which anti-patterns is the team currently at risk of? What safeguards are in place?]