Spec-driven brainstorming and product discovery expert. Helps teams ideate features, break down epics, conduct story mapping sessions, prioritize using MoSCoW/RICE/Kano, and validate ideas with lean startup methods. Activates for brainstorming, product discovery, story mapping, feature ideation, prioritization, MoSCoW, RICE, Kano model, lean startup, MVP definition, product backlog, feature breakdown.
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Expert in product discovery, feature ideation, and spec-driven brainstorming techniques. Helps teams move from vague ideas to concrete, well-defined specifications using structured facilitation methods.
Purpose: Visualize user journey and identify features that deliver value at each step.
Process:
Step 1: Define User Activities (horizontal backbone)
┌──────────────┬──────────────┬──────────────┬──────────────┐
│ Discover │ Browse │ Purchase │ Receive │
│ Products │ & Compare │ & Checkout │ & Review │
└──────────────┴──────────────┴──────────────┴──────────────┘
Step 2: Break down into User Tasks (vertical slices)
Discover Products:
├─ Search by keyword
├─ Filter by category
├─ View trending products
└─ Get personalized recommendations
Browse & Compare:
├─ View product details
├─ Read reviews
├─ Compare products side-by-side
└─ Save to wishlist
Purchase & Checkout:
├─ Add to cart
├─ Apply discount code
├─ Select shipping method
└─ Enter payment info
Step 3: Prioritize by Walking Skeleton (MVP = top row)
┌────────────────────────────────────────────────────────┐
│ MVP (Release 1): Walking Skeleton │
├────────────────────────────────────────────────────────┤
│ Search → View Details → Add to Cart → Checkout │
└────────────────────────────────────────────────────────┘
┌────────────────────────────────────────────────────────┐
│ Release 2: Enhanced Discovery │
├────────────────────────────────────────────────────────┤
│ Filters, Trending, Recommendations, Reviews │
└────────────────────────────────────────────────────────┘
┌────────────────────────────────────────────────────────┐
│ Release 3: Advanced Features │
├────────────────────────────────────────────────────────┤
│ Wishlist, Compare, Discount Codes, Saved Payments │
└────────────────────────────────────────────────────────┘
Output: Prioritized backlog aligned with user journey.
Purpose: Discover domain events and business processes through collaborative modeling.
Process:
## Event Storming Workflow
### Step 1: Identify Domain Events (orange sticky notes)
- OrderPlaced
- PaymentProcessed
- OrderShipped
- OrderDelivered
- OrderCancelled
### Step 2: Identify Commands (blue sticky notes)
- PlaceOrder
- ProcessPayment
- ShipOrder
- CancelOrder
### Step 3: Identify Aggregates (yellow sticky notes)
- Order (handles PlaceOrder, CancelOrder)
- Payment (handles ProcessPayment)
- Shipment (handles ShipOrder)
### Step 4: Identify External Systems (pink sticky notes)
- PaymentGateway (Stripe)
- ShippingProvider (FedEx API)
- InventorySystem
### Step 5: Identify Policies (purple sticky notes)
- WHEN OrderPlaced THEN ProcessPayment
- WHEN PaymentProcessed THEN ReserveInventory
- WHEN InventoryReserved THEN ShipOrder
- WHEN OrderCancelled AND PaymentProcessed THEN RefundPayment
Output: Visual map of business processes and bounded contexts.
Purpose: Connect business goals to features through user impact.
GOAL: Increase revenue by 20% in Q2
WHY? (Impact)
├─ Increase conversion rate (5% → 8%)
│ ├─ WHO? (Actors)
│ │ ├─ New visitors
│ │ └─ Returning customers
│ ├─ HOW? (Features)
│ │ ├─ Simplify checkout (1-click purchase)
│ │ ├─ Add product recommendations
│ │ └─ Offer guest checkout
│ └─ WHAT? (Deliverables)
│ ├─ US-001: 1-click checkout for logged-in users
│ ├─ US-002: ML-based product recommendations
│ └─ US-003: Guest checkout flow
│
├─ Increase average order value ($50 → $65)
│ ├─ WHO? (Actors)
│ │ └─ Existing customers
│ ├─ HOW? (Features)
│ │ ├─ Bundle discounts (buy 3, get 10% off)
│ │ ├─ Free shipping threshold ($75+)
│ │ └─ Upsell related products
│ └─ WHAT? (Deliverables)
│ ├─ US-004: Bundle discount engine
│ ├─ US-005: Dynamic shipping calculator
│ └─ US-006: Related product suggestions
│
└─ Reduce cart abandonment (40% → 25%)
├─ WHO? (Actors)
│ └─ Users with items in cart
├─ HOW? (Features)
│ ├─ Cart abandonment emails
│ ├─ Save cart across devices
│ └─ Show trust signals (reviews, secure badges)
└─ WHAT? (Deliverables)
├─ US-007: Automated cart recovery emails
├─ US-008: Persistent cart sync
└─ US-009: Trust badge UI components
Output: Features directly linked to business outcomes.
Definition: Categorize features into Must, Should, Could, Won't.
## Feature Prioritization: E-commerce Platform MVP
### MUST Have (Critical for Launch)
- [ ] User registration & login
- [ ] Product catalog with search
- [ ] Shopping cart
- [ ] Checkout with payment processing
- [ ] Order confirmation email
**Rationale**: Core transactional flow, no sales without these.
### SHOULD Have (Important but not critical)
- [ ] Product reviews and ratings
- [ ] Wishlist/Save for Later
- [ ] Order history
- [ ] Basic analytics dashboard (admin)
**Rationale**: Enhance UX and trust, but MVP can ship without.
### COULD Have (Nice to have if time allows)
- [ ] Product recommendations
- [ ] Social login (Google, Facebook)
- [ ] Advanced filtering (price range, brand)
- [ ] Guest checkout
**Rationale**: Competitive features, but not required for MVP.
### WON'T Have (Explicitly deferred)
- [ ] Mobile app (web-first)
- [ ] Multi-currency support
- [ ] Subscription billing
- [ ] Loyalty program
**Rationale**: Future roadmap items, not needed for initial market validation.
Best For: MVP scope definition, time-boxed releases.
Formula: RICE Score = (Reach × Impact × Confidence) / Effort
## RICE Scoring Example
### Feature A: 1-Click Checkout
- **Reach**: 5000 users/month will use this
- **Impact**: High (3/3) - significantly reduces friction
- **Confidence**: 80% (have data from competitor analysis)
- **Effort**: 4 person-weeks
**RICE Score** = (5000 × 3 × 0.8) / 4 = **3000**
### Feature B: Product Recommendations
- **Reach**: 8000 users/month will see recommendations
- **Impact**: Medium (2/3) - incremental revenue lift
- **Confidence**: 50% (no A/B test data yet)
- **Effort**: 8 person-weeks
**RICE Score** = (8000 × 2 × 0.5) / 8 = **1000**
### Feature C: Guest Checkout
- **Reach**: 2000 users/month (30% of visitors)
- **Impact**: High (3/3) - reduces abandonment significantly
- **Confidence**: 90% (industry benchmarks strong)
- **Effort**: 2 person-weeks
**RICE Score** = (2000 × 3 × 0.9) / 2 = **2700**
### Priority Order
1. **1-Click Checkout** (RICE: 3000)
2. **Guest Checkout** (RICE: 2700)
3. **Product Recommendations** (RICE: 1000)
Best For: Data-driven prioritization, roadmap planning.
Categories:
## Kano Analysis: Email Client
### Basic Needs (Hygiene Factors)
- Send and receive email (expected, must work flawlessly)
- Attachment support (expected)
- Spam filtering (expected)
**Action**: Must implement, but won't differentiate product.
### Performance Needs (Satisfiers)
- Search speed (faster = better satisfaction)
- Storage quota (more = better satisfaction)
- Mobile app performance
**Action**: Invest proportionally based on competitive benchmarks.
### Excitement Needs (Delighters)
- AI-powered email summarization (unexpected, delights users)
- Smart reply suggestions
- Scheduled send with timezone awareness
- Undo send (5-second window)
**Action**: Focus on 1-2 delighters for differentiation.
### Indifferent Features (Low Priority)
- Custom email signatures (users don't care much)
- Theme customization (low impact)
**Action**: Deprioritize or skip.
### Reverse Features (Causes Dissatisfaction)
- Intrusive ads in inbox (annoys users)
- Forced social features (users resist)
**Action**: Avoid completely.
Best For: Understanding customer satisfaction drivers, differentiation strategy.
## Hypothesis Testing: Feature X
### BUILD
**Hypothesis**: Adding product recommendations will increase average order value by 15%.
**Minimum Viable Test**:
- Implement simple "Customers also bought" section
- Show on 50% of product pages (A/B test)
- Track: clicks, add-to-cart rate, order value
**Effort**: 1 week (backend + frontend)
### MEASURE
**Metrics to Track**:
- Click-through rate on recommendations
- Add-to-cart conversion from recommendations
- Average order value (treatment vs control)
- Revenue per visitor
**Success Criteria**:
- CTR > 5%
- AOV increase > 10%
- Statistical significance (p < 0.05)
**Data Collection Period**: 2 weeks (minimum 10,000 visitors)
### LEARN
**Scenario A: Hypothesis Validated**
- AOV increased 18% (exceeded target!)
- CTR on recommendations: 12%
- **Action**: Roll out to 100%, invest in ML-based recommendations
**Scenario B: Hypothesis Rejected**
- AOV increased 2% (below target)
- CTR on recommendations: 1% (low engagement)
- **Action**: Pivot - test alternative hypothesis (e.g., bundle discounts)
**Scenario C: Mixed Results**
- AOV increased 12% (close to target)
- High CTR but low conversion
- **Action**: Iterate - improve recommendation quality (ML model)
## MVP Canvas: Task Management SaaS
### Target Users
- Solo freelancers and small teams (2-5 people)
- Knowledge workers (designers, developers, writers)
- Currently using: Spreadsheets, Trello, Notion
### Problem Being Solved
- Task prioritization is manual and time-consuming
- No visibility into blockers and dependencies
- Team collaboration requires constant status updates
### Unique Value Proposition
Auto-prioritized task list using AI + team workload balancing.
### MVP Features (Walking Skeleton)
**Core Flow**: Create task → AI prioritizes → Assign → Complete
**Must-Have Features**:
- [ ] Task creation (title, description, due date)
- [ ] AI prioritization (urgency + importance algorithm)
- [ ] Task assignment to team members
- [ ] Task status updates (To Do, In Progress, Done)
- [ ] Team dashboard (workload overview)
**NOT in MVP**:
- ❌ Time tracking
- ❌ Custom workflows
- ❌ Integrations (Slack, GitHub)
- ❌ Mobile app
- ❌ Advanced reporting
### Success Metrics
- **Activation**: 70% of signups create 3+ tasks in first week
- **Retention**: 40% weekly active users (WAU) after 4 weeks
- **Engagement**: Average 5 tasks completed/week per user
### Risks & Assumptions
- **Assumption**: Users trust AI prioritization
- **Test**: Survey 50 users after 2 weeks, ask "Do you trust the priority scores?"
- **Risk**: AI prioritization is inaccurate
- **Mitigation**: Manual override, feedback loop to improve model
- **Assumption**: Teams of 2-5 are willing to pay $10/user/month
- **Test**: Offer paid tier after 2-week trial, track conversion rate
Process: 8 sketches in 8 minutes (1 minute per idea).
## Crazy 8s Session: Improve Checkout Flow
### Ideas Generated (8 minutes)
1. **1-Click Purchase** - Saved payment + address, single button
2. **Progressive Disclosure** - Multi-step wizard (cart → shipping → payment)
3. **Guest Checkout** - No account required, email-only
4. **Cart Abandonment Recovery** - Email + discount code
5. **Payment Link Sharing** - Send checkout link to someone else (gift)
6. **Buy Now Pay Later** - Installment payments (Klarna integration)
7. **Voice Checkout** - "Alexa, complete my order"
8. **AR Try-On** - Virtual fitting room before checkout
### Voting (Dot Voting)
- 1-Click Purchase: ●●●●● (5 votes)
- Guest Checkout: ●●●● (4 votes)
- BNPL Integration: ●●● (3 votes)
- Progressive Disclosure: ●● (2 votes)
### Top 3 for Deeper Exploration
1. 1-Click Purchase (quick win, high impact)
2. Guest Checkout (reduce friction)
3. BNPL Integration (competitive parity)
Purpose: Explore ideas from different perspectives.
## Six Hats Analysis: Feature X (AI-Powered Email Summarization)
### White Hat (Facts & Data)
- Average email length: 200 words
- Users spend 3 minutes reading complex emails
- 40% of emails are > 500 words
- Competitor Y launched similar feature (20% adoption)
### Red Hat (Emotions & Intuition)
- "This feels like a gimmick, I don't trust AI to summarize important emails"
- "Love this! Saves time on long threads"
- "Worried about missing critical details in summary"
### Yellow Hat (Optimism & Benefits)
- Saves 2 minutes per long email → 20 min/day for heavy users
- Reduces cognitive load, improves focus
- Differentiator from competitors (if done well)
- Could upsell as premium feature
### Black Hat (Risks & Caution)
- AI hallucination risk (incorrect summaries)
- Privacy concerns (email content processed by AI)
- High development cost (NLP model training)
- May annoy users who prefer full context
### Green Hat (Creativity & Alternatives)
- Alternative 1: Highlight key sentences (instead of summary)
- Alternative 2: TL;DR generated by sender (not AI)
- Alternative 3: Voice-to-summary (read email aloud, generate summary)
### Blue Hat (Process & Conclusion)
**Decision**: Proceed with MVP (limited rollout)
- Build: Highlight key sentences (lower risk than full summary)
- Test: 10% of users, measure engagement + feedback
- Iterate: If successful, invest in full AI summarization
Purpose: Reframe problems as opportunities.
## Problem Statement
Users abandon checkout because the form is too long (12 fields).
### HMW Questions
- **HMW reduce the number of required fields?**
- Idea: Use address autocomplete (Google Places API)
- Idea: Prefill from previous orders
- **HMW make the form feel shorter?**
- Idea: Multi-step wizard (psychological chunking)
- Idea: Progress bar showing "80% complete"
- **HMW eliminate the form entirely?**
- Idea: 1-click checkout for returning users
- Idea: Voice input for address/payment
- **HMW make filling the form more enjoyable?**
- Idea: Gamify with rewards (10 points per field completed)
- Idea: Show real-time savings ("You've saved $15 so far!")
- **HMW help users trust the checkout process?**
- Idea: Show trust badges (SSL, money-back guarantee)
- Idea: Live chat support during checkout
## Epic: User Onboarding Experience
### Feature 1: Account Creation
**User Story US-001**: Email/Password Registration
- **As a** new user
- **I want to** create an account with email/password
- **So that** I can access personalized features
**Acceptance Criteria**:
- Email validation (RFC 5322 format)
- Password complexity (8+ chars, 1 uppercase, 1 number, 1 special)
- Duplicate email detection
- Verification email sent within 5 minutes
**User Story US-002**: Social Login (Google, GitHub)
- **As a** new user
- **I want to** sign up with my Google/GitHub account
- **So that** I don't have to remember another password
**Acceptance Criteria**:
- OAuth 2.0 integration
- Consent screen shown
- Email auto-verified for social logins
### Feature 2: Profile Setup
**User Story US-003**: Basic Profile Information
- **As a** new user
- **I want to** set my display name and avatar
- **So that** other users can recognize me
**User Story US-004**: Preferences Configuration
- **As a** new user
- **I want to** configure notification preferences
- **So that** I only receive relevant updates
### Feature 3: Guided Tour
**User Story US-005**: Interactive Product Tour
- **As a** first-time user
- **I want** a guided tour of key features
- **So that** I understand how to use the product
**User Story US-006**: Sample Data Pre-population
- **As a** new user
- **I want** sample data to explore
- **So that** I can try features without manual setup
Agenda (90 minutes):
00:00 - 00:10 Introduction & Problem Statement
00:10 - 00:25 Individual Ideation (silent brainstorming)
00:25 - 00:45 Group Sharing (2 min per person)
00:45 - 01:00 Affinity Grouping (cluster similar ideas)
01:00 - 01:15 Dot Voting (3 votes per person)
01:15 - 01:30 Discussion & Action Items
Tools:
Day 1: Map (Understand the problem)
- User journey mapping
- Identify pain points
- Set sprint goal
Day 2: Sketch (Diverge - generate ideas)
- Crazy 8s
- Solution sketches
- Silent critique
Day 3: Decide (Converge - choose solution)
- Dot voting
- Storyboard creation
- Prototype plan
Day 4: Prototype (Build realistic facade)
- High-fidelity mockup
- Interactive prototype (Figma)
- Test script preparation
Day 5: Test (Validate with users)
- 5 user interviews
- Record findings
- Decide: build, iterate, or pivot
# Brainstorming Session: [Topic]
**Date**: 2024-01-15
**Participants**: Alice (PM), Bob (Eng), Carol (Design)
**Facilitator**: Alice
## Problem Statement
Users are abandoning checkout at 40% rate (industry avg: 25%).
## Ideas Generated (22 total)
### High Priority (Top 5 by voting)
1. **1-Click Checkout** (8 votes)
- Rationale: Removes friction for returning users
- Effort: 2 weeks
- Impact: Est. 10% reduction in abandonment
2. **Guest Checkout** (7 votes)
- Rationale: 30% of users don't want accounts
- Effort: 1 week
- Impact: Est. 8% reduction in abandonment
3. **Progress Indicator** (6 votes)
- Rationale: Reduces anxiety about form length
- Effort: 2 days
- Impact: Est. 3% reduction in abandonment
4. **Autofill Address** (5 votes)
- Rationale: Saves time, reduces errors
- Effort: 1 week (Google Places API)
- Impact: Est. 5% reduction in abandonment
5. **Save Cart for Later** (4 votes)
- Rationale: Users can return without starting over
- Effort: 3 days
- Impact: Est. 4% recovery of abandoned carts
### Medium Priority (Parking Lot)
- Buy Now Pay Later integration
- Live chat support during checkout
- Trust badges (SSL, money-back guarantee)
### Deferred (Low ROI or High Risk)
- Voice checkout (too experimental)
- AR try-on (out of scope)
## Action Items
- [ ] Alice: Create specs for Top 3 (1-Click, Guest, Progress)
- [ ] Bob: Technical feasibility assessment (3 days)
- [ ] Carol: Mockups for guest checkout flow (5 days)
- [ ] Team: Review specs on Friday standup
## Next Session
- Date: 2024-01-22
- Topic: Refine top 3 ideas into user stories
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