discovery-process

name	discovery-process
description	Run a compressed 5-day product discovery cycle. Use when validating whether a problem is worth solving before committing engineering resources.

Discovery Process

A structured discovery cycle compressed from the traditional 3-4 weeks to 5 focused days. AI handles synthesis and framework execution; you handle user conversations and judgment calls.

When to Use

• You've identified a potential problem or opportunity but haven't validated it
• Leadership is asking "should we build this?" and you need evidence
• You're entering a new market or user segment and need to understand needs
• Churn data, support tickets, or feedback suggest a problem but you don't know the root cause
• You need to choose between multiple possible initiatives

When NOT to Use

• The problem is already validated and you need to write a spec — go to your PRD template
• You're optimizing an existing feature with clear metrics — use Growth & Retention Diagnostics
• You need stakeholder buy-in for something already validated — use Stakeholder Alignment

The AI-Native Approach

Traditional discovery: 3-4 week dedicated sprint. Most time spent on synthesis, documentation, and alignment meetings.

AI-native discovery: 5 focused days. Claude compresses synthesis and documentation to hours. Your time goes to the irreplaceable human work — talking to users, applying judgment, and making the call.

Day	Focus	Time	Claude Does	You Do
1	Frame the problem	2-3 hrs	Structure raw signals, identify assumptions	Provide context, validate framing
2	Synthesize existing data	2-3 hrs	Synthesize analytics, feedback, competitive data	Review against your knowledge
3	Talk to users	Half day	Prepare discussion guide, synthesize notes after	Conduct 3-5 interviews
4	Map opportunities	2-3 hrs	Build opportunity solution tree, rank by evidence	Decide which branch to pursue
5	Decide	1-2 hrs	Draft spec or experiment brief	Make the build/validate/kill call

Process

Day 1: Frame the Problem (2-3 hours)

Bring your raw signals — support tickets, usage data, user quotes, business context.

Here's what I'm seeing: [raw signals — paste data, quotes, metrics].

Help me frame this as a problem statement:
- Who is affected and how many?
- What's the evidence (data vs. inference vs. assumption)?
- What are we assuming that we haven't validated?
- What's the business impact if we don't address this?

Review Claude's output. Challenge the framing: does this match what you're hearing from users, or is Claude over-fitting to the loudest signals?

Day 2: Synthesize What You Know (2-3 hours)

Feed Claude your existing data sources. Don't generate new research — synthesize what already exists.

Here are our data sources on this problem:
- [Analytics data / dashboard exports]
- [Support ticket themes from the last 90 days]
- [Survey responses or NPS verbatims]
- [Competitive context]

Synthesize the key findings:
- What patterns emerge across sources?
- Where do sources agree or conflict?
- Rate evidence strength: strong (data-backed), moderate (inferred), weak (assumed)
- What are the critical gaps we need to fill with primary research?

Day 3: Talk to Users (half day)

This step cannot be compressed or delegated. Talk to 3-5 users.

Based on our problem statement and the gaps identified yesterday, generate a
discussion guide for 30-minute user interviews.

Requirements:
- Focus questions on [specific gaps identified]
- Use past-behavior questions, not hypotheticals
- Include one "surprise me" open-ended question
- Flag any questions that might lead the witness
- Keep it to 8-10 questions max

After interviews, feed your notes back:

Here are my notes from [N] user interviews. Identify:
- Themes that appeared across multiple interviews
- Contradictions between users
- Surprises — anything that challenges our assumptions
- Quotes worth preserving for stakeholder communication

Day 4: Map Opportunities and Rank (2-3 hours)

Based on our research synthesis and interview findings, build an opportunity
solution tree:

Desired outcome: [measurable outcome — e.g., "reduce onboarding drop-off from 40% to 25%"]

For each opportunity:
- 2-3 possible solutions
- Evidence strength supporting this opportunity
- Simplest experiment that would validate each solution
- Estimated effort and impact

Rank opportunities by evidence strength × potential impact.

Review the tree. Override the ranking when your strategic context says otherwise.

Day 5: Decide (1-2 hours)

Three possible outcomes:

Build: Evidence is strong. Ask Claude to draft the PRD from your discovery artifacts.

Validate further: Evidence is promising but thin. Ask Claude to draft an experiment brief.

Kill: Evidence doesn't support the hypothesis. Document why and move on.

Based on our 5-day discovery, draft a [PRD / experiment brief / decision memo]
that captures:
- The problem and evidence
- What we learned from users
- The recommended path forward
- What we're explicitly choosing NOT to do and why

Output

• Structured problem statement with evidence ratings
• Research synthesis with gap analysis
• User interview themes and key quotes
• Opportunity solution tree with ranked options
• PRD, experiment brief, or kill decision memo

Common Pitfalls

1. Skipping user interviews to save time. Days 1-2 and 4-5 can be compressed further. Day 3 cannot. Talking to users is the entire point.
2. Treating Claude's synthesis as ground truth. Claude identifies patterns in the data you provide. It can't tell you about the user who churned silently or the competitor move that hasn't been announced.
3. Falling in love with the first opportunity. The tree exists to keep options open. Don't collapse to a solution before you've evaluated alternatives.
4. Discovery as delay tactic. 5 days is the limit. If you need more time, you're probably avoiding a decision, not gathering evidence.

Related Skills

• Product Strategy & Vision — when discovery feeds into strategic planning
• User Research Methods — for deeper research beyond the 5-day cycle
• Stakeholder Alignment — when discovery findings need stakeholder buy-in
• Reference: FRAMEWORKS.md — JTBD, Opportunity Solution Trees, Customer Journey Mapping
• Reference: TEMPLATES.md — PRD and Experiment Brief templates