product-execution

Product Execution — Strategy-to-Product Bridge

Purpose

This skill bridges the gap between strategic analysis (market research, competitive landscape, AJTBD) and actionable product development. It converts strategy documents into opportunity trees, feature specifications, prioritized roadmaps, MVP definitions, and story maps.

When This Skill Applies

• After strategy analysis is complete and product planning begins
• Creating feature specifications from identified opportunities
• Building or updating product roadmaps
• Defining MVP scope and success criteria
• Mapping user stories from jobs-to-be-done analysis
• Prioritizing features using WSJF, Kano, or MoSCoW
• Designing opportunity solution trees from strategy insights

Core Principles

1. Opportunity-First Thinking

Never start with a solution. Start with the opportunity:

1. Identify the outcome you want to drive (from strategy docs)
2. Map the opportunities that could move that outcome (from jobs-graph problems)
3. Generate solutions for the highest-value opportunities
4. Test assumptions before committing to build

Features without a traced opportunity are waste.

2. Shape Up Pitch Format

Use Ryan Singer's Shape Up pitch as the default feature specification format:

• Problem — linked to a specific job and problem from jobs-graph.md
• Appetite — time budget that constrains the solution (not an estimate)
• Solution — low-fidelity description of approach (enough to evaluate, not enough to implement)
• Rabbit Holes — known risks and complexity traps
• No-Gos — explicit exclusions

Appetite is not an estimate. Estimates answer "how long will this take?" Appetite answers "how much time is this problem worth?"

3. WSJF Scoring for Feature Prioritization

Use Weighted Shortest Job First (WSJF) to prioritize features in the roadmap:

• Cost of Delay = User/Business Value + Time Criticality + Risk Reduction
• WSJF = Cost of Delay / Job Duration
• Score relative to other features, not absolute

4. Kano Categorization

Classify every feature by its satisfaction profile:

• Must-Be: absence causes dissatisfaction, presence is expected
• Performance: linear relationship — more is better
• Attractive: delighters — absence is neutral, presence creates joy
• Indifferent: no impact — do not build
• Reverse: presence causes dissatisfaction — avoid

5. Cross-Reference Everything

Every feature must trace back through the strategy document chain:

Feature → Opportunity → Job + Problem → Segment → Strategy Insight

If you cannot draw this line, the feature lacks strategic justification.

The Bridge Pattern

Strategy documents feed into product execution in a specific order:

Strategy Docs          Product Execution
─────────────          ─────────────────
strategy-canvas.md ──→ Desired Outcomes
jobs-graph.md ───────→ Opportunities (problems with severity >7)
rat.md ──────────────→ Assumption Tests (map risks to solutions)
customer-segments.md → Target Users (who gets the feature first)
growth-plan.md ──────→ Success Metrics (North Star, AARRR)
business-model.md ───→ Revenue Constraints (pricing, unit economics)
                       ↓
                   Opportunity Tree → Feature Specs → Roadmap → MVP → Story Map

Reference Map

Reference File	Purpose	When to Use
references/opportunity-trees.md	Teresa Torres Opportunity Solution Tree methodology	When mapping outcomes to opportunities to solutions
references/feature-specification.md	Shape Up pitch + Amazon PR/FAQ + Cagan lightweight spec	When writing feature specifications
references/roadmap-methods.md	Now/Next/Later, Kano Model, WSJF scoring	When prioritizing and sequencing features
references/mvp-definition.md	MoSCoW prioritization, lean MVP, validation planning	When scoping an MVP or defining launch criteria
references/story-mapping.md	Jeff Patton story mapping, job stories	When breaking features into implementable stories

Key Distinction: ICE/RICE vs WSJF

Framework	Use For	Owned By	Reference
ICE/RICE	Growth experiments — short-lived tests with measurable outcomes	growth-strategist	strategy-overture/references/growth-experiments.md
WSJF	Feature prioritization — committed product roadmap items	product-planner	product-execution/references/roadmap-methods.md

Do not use ICE/RICE to prioritize features. Do not use WSJF to prioritize experiments. The frameworks solve different problems.

Cross-Reference Rules

Every feature specification must include a traceability table:

Field	Source Document	Specific Reference
Job	jobs-graph.md	Job [X]: [name]
Segment	customer-segments.md	[segment name]
Problem	jobs-graph.md	Problem [Y]: [description], Severity [Z]
Risk	rat.md	Risk Card [N]: [name], Score [P x I]
Strategy	strategy-canvas.md	[ERRC action]: [factor]
Initiative	prioritized-initiatives.md	Initiative [N]: [name]

If any cell is empty, the feature lacks strategic grounding. Either find the linkage or question whether the feature should exist.

Anti-Patterns

Anti-Pattern	Why It Fails	Correct Approach
Features without job linkage	Building what nobody asked for — solution-first thinking	Every feature traces to a job + problem from jobs-graph.md
Roadmap without prioritization scores	No defensible ordering — squeaky wheel gets resources	Score every item with WSJF before sequencing
MVP without success metrics	Cannot determine if MVP succeeded — endless iteration	Define kill criteria before writing a single line of code
Skipping Opportunity Tree	Jumping from outcome to solution misses better alternatives	Always generate 3+ solutions per opportunity, then pick
Appetite as estimate	Teams gold-plate because scope is unbounded	Set appetite first, shape solution to fit within it
Story map without backbone	Disconnected stories with no user journey context	Build the backbone (activities) first, then slice releases
All features as Must-Have	MoSCoW becomes meaningless — everything is critical	Must-Haves should be ~60% of effort; if more, re-evaluate
Roadmap as commitment	Dates on Later items create false expectations	Now/Next/Later format — only Now has dates