shaping-product-strategy

name	shaping-product-strategy
description	Shapes product decisions through tiered frameworks -- Shape Up for features, DIBB+PR/FAQ for strategic bets, ICE for prioritization, and Opportunity Solution Trees for discovery. Use when writing feature specs, evaluating strategic bets, prioritizing the roadmap, or running product discovery.
version	1
tags	["product","strategy","prioritization","discovery","api-design"]
triggers	["write a feature spec","shape a feature","evaluate a strategic bet","prioritize the roadmap","run product discovery","design an API endpoint","should we build X or Y","DIBB analysis","ICE score","PR/FAQ"]
cross-references	[{"skill":"measuring-growth","relationship":"ICE experiment backlog feeds growth sprints"},{"skill":"launching-go-to-market","relationship":"DIBB bets feed GTM strategy"},{"skill":"steering-strategy","relationship":"DIBB for company-level strategic bets"},{"skill":"validating-ideas","relationship":"Feeds validated ideas into product discovery"}]

Skill: Shaping Product Strategy

You are a product strategist for [YOUR_COMPANY]. Adapt the context below to match your company's domain, product portfolio, and target market.

Team context: Small team (3-6 people). Shape Up's 6-week appetite concept fits a small team perfectly. Every framework output must be actionable by a small team -- no bureaucracy, no 20-page documents.

Product roadmap sequence: Define your own product launch order, e.g., [Product A] > [Product B] > [Product C] > [Product D].

---

Framework Selection Guide

Pick the right tier based on the decision scope:

Scope	Framework	When to Use	Output
Feature	Shape Up Pitch	Building a specific capability (e.g., "add [Product B] endpoint")	Pitch document
Strategic bet	DIBB + PR/FAQ	Evaluating a direction (e.g., "B2B vs B2C", "enter new market")	Bet analysis + kill criteria
Prioritization	ICE Scorecard	Ranking multiple items against each other	Scored & ranked table
Discovery	Opportunity Solution Tree	Exploring a problem space before committing	Visual tree + test plan
API endpoint	API Product Spec	Designing or extending the API surface	Developer-ready spec

If unsure which tier, ask: "Is this about WHAT to build (discovery), WHETHER to build (bet), HOW to build (feature), or WHAT ORDER to build (prioritization)?"

---

1. Shape Up Pitch (Feature-Level)

Use for features with a clear problem that need shaping before engineering begins. Based on Basecamp's Shape Up methodology.

When to Use

• A feature request has been validated but needs scoping
• Moving an item from backlog to "ready for build"
• Defining appetite (time budget) before committing engineering time

Template

# Shape Up Pitch: [Feature Name]

## Problem
What is the user/developer pain point? Be specific.
- Who experiences this? (developer, end-user, ops team)
- How do they work around it today?
- What evidence do we have? (support tickets, interview quotes, usage data)

## Appetite
How much time are we willing to spend? Pick one:
- [ ] Small Batch: 1-2 weeks (bug fix, minor enhancement)
- [ ] Medium Batch: 2-4 weeks (new endpoint, significant feature)
- [ ] Big Batch: 6 weeks (new product vertical, major system change)

Appetite is NOT an estimate. It is a budget. If it cannot ship within the
appetite, reshape or kill.

## Solution
Sketch the approach at the right level of abstraction.
- Fat-marker sketch (broad strokes, not wireframes)
- Key interactions or API surface changes
- How it fits into the existing system

## Non-Goals (Explicitly Out of Scope)
- What are we NOT building in this cycle?
- What adjacent features are we deferring?

## Rabbit Holes
Risks that could blow up the appetite:
- [ ] Risk 1: [description] -- Mitigation: [approach]
- [ ] Risk 2: [description] -- Mitigation: [approach]
- [ ] Risk 3: [description] -- Mitigation: [approach]

## DX Checklist (for developer-facing products)
For any developer-facing feature, verify:
- [ ] Can a developer understand this from the API docs alone?
- [ ] Does it work in test mode identically to production?
- [ ] Does it follow existing naming conventions? (RESTful, consistent with other endpoints)
- [ ] Is there a clear error response for every failure case?
- [ ] Does it avoid breaking changes to existing endpoints?
- [ ] Time to integrate: can a developer ship this in < 1 day?

## Go/No-Go
- [ ] Problem is validated (evidence above)
- [ ] Appetite is set and accepted
- [ ] Solution is shaped (not over-specified)
- [ ] Rabbit holes are identified and mitigated
- [ ] DX checklist passes

Product Evolution Guidance

Tony Fadell's Three Generations Rule applied to product verticals:

• V1 (Walking Skeleton): Get your core product working end-to-end. Prove the thesis. Shipping > polish.
• V2 (Expand): Add adjacent products. Solidify the platform. Developer/user experience becomes the differentiator.
• V3 (Full Platform): Complete product breadth. Network effects kick in.

Stripe API Design Philosophy (for API-first companies):

• Never deprecate without a migration path. Breaking changes are product failures.
• Test mode is a first-class citizen. Every endpoint works identically in sandbox.
• Friction logging: track every point where a developer gets stuck during integration.
• Idempotency keys on all mutating operations. Developers must be able to retry safely.
• Consistent pagination, error formats, and naming across all product verticals.

---

2. DIBB Chain + PR/FAQ (Strategic Bets)

Use for decisions that change company direction. Combines Spotify's DIBB framework with Amazon's PR/FAQ for rigorous bet evaluation.

When to Use

• Evaluating B2B vs B2C as a strategic direction
• Deciding whether to enter a new market
• Choosing between building vs partnering for a capability
• Any decision that is irreversible or expensive to reverse (Type 1 decision)

Template

# Strategic Bet: [Title]

## DIBB Chain

### Data
What do we observe? Facts only, no interpretation.
- Market data: [size, growth, trends]
- Customer signals: [requests, usage patterns, churn reasons]
- Competitive moves: [what competitors are doing]
- Internal metrics: [pipeline, conversion, revenue data]

### Insight
What does the data mean? Connect the dots.
- Pattern: [what pattern emerges from the data?]
- So what: [why does this pattern matter for our company?]

### Belief
Based on the insight, what do we believe to be true?
- "We believe that [hypothesis] because [insight]."
- Conviction level: Low / Medium / High
- What would change our mind: [falsification criteria]

### Bet
What are we going to do about it?
- Action: [specific initiative or direction]
- Investment: [time, money, people required]
- Timeline: [when we will know if this is working]
- Opportunity cost: [what we are NOT doing by choosing this]

---

## PR/FAQ (Amazon-Style)

### Press Release (The Future State)

**FOR IMMEDIATE RELEASE**

**[City, Date]** -- [YOUR_COMPANY] today announced [the thing we built/launched].

[One paragraph: what is it and who is it for?]

[One paragraph: what problem does it solve? Include a quote from a fictional
 customer or partner.]

[One paragraph: how does it work at a high level?]

[One paragraph: what makes this different from alternatives?]

"[Quote from leadership on why this matters]"

[Availability and next steps.]

### FAQ -- Customer Questions (answer 5 most likely)
1. Q: [Most obvious customer question] -- A: [Answer]
2. Q: [Pricing/cost question] -- A: [Answer]
3. Q: [Integration/migration question] -- A: [Answer]
4. Q: [Competitive alternative question] -- A: [Answer]
5. Q: [Timeline/availability question] -- A: [Answer]

### FAQ -- Internal/Stakeholder Questions
1. Q: Why now? -- A: [Answer with data reference]
2. Q: What if it fails? -- A: [Answer with kill criteria reference]
3. Q: What are we NOT doing because of this? -- A: [Explicit opportunity cost]
4. Q: How does this affect existing customers? -- A: [Answer]
5. Q: What is the minimum investment to test this? -- A: [Staged approach]

---

## Kill Criteria

Define upfront when to abandon this bet:

| Metric | Target | Kill Threshold | Check Date |
|--------|--------|----------------|------------|
| [Metric 1] | [Target] | [Below this, we stop] | [Date] |
| [Metric 2] | [Target] | [Below this, we stop] | [Date] |
| [Metric 3] | [Target] | [Below this, we stop] | [Date] |

**Sunk cost reminder:** If kill criteria are met, we stop. Period. The resources
spent are already gone. The question is only: "Given what we know NOW, would we
start this bet today?"

## Decision

- [ ] Approved -- proceed to execution
- [ ] Rejected -- document why, archive
- [ ] Needs more data -- specify what data and by when

DIBB Examples

B2B vs B2C Fork: A common consequential strategic bet for platform companies. DIBB structures it:

• Data: B2B pipeline has X qualified leads; B2C requires consumer app, support, compliance
• Insight: B2B has faster path to revenue; B2C has larger TAM but 10x higher burn
• Belief: B2B first for 12-18 months builds the infrastructure that B2C later runs on
• Bet: Commit to B2B. Revisit B2C only when ARR > $[threshold] or a strategic trigger occurs

New Product Vertical: When evaluating whether to add a new product to the platform:

• Data: Which providers are ready? What do pipeline clients request?
• Insight: Provider readiness + client demand intersection
• Belief: [Product X] has the highest demand-to-effort ratio
• Bet: Ship [Product X] in [N weeks], measure adoption in first 3 clients

---

3. ICE Scorecard (Prioritization)

This is the primary home for ICE scoring across all skills. Growth & Analytics references ICE but does not own it.

Use to rank competing items -- features, experiments, bugs, or bets -- against each other on a level playing field.

When to Use

• Quarterly/monthly roadmap prioritization or ranking 5+ backlog items
• Choosing experiments for a growth sprint or answering "what should we work on next?"

Scoring Guide (1-10 per dimension, be honest -- inflated scores defeat the purpose)

Impact (1-10): How much does this move a key metric?

Score	Meaning
1-2	Nice-to-have, minimal metric movement
3-4	Improves experience for a subset of users
5-6	Meaningful improvement to a key metric (activation, conversion, retention)
7-8	Significant revenue or retention impact across most clients
9-10	Existential: unlocks a new market, unblocks pipeline, or prevents churn

Confidence (1-10): How sure are we about the impact estimate?

Score	Meaning
1-2	Pure gut feeling, no data
3-4	Anecdotal evidence (1-2 customer conversations)
5-6	Qualitative validation (multiple interviews, competitor analysis)
7-8	Quantitative signals (usage data, A/B test on related feature, survey)
9-10	Direct evidence (customers pre-committed, proven in test environment)

Ease (1-10): How quickly can we ship this with current resources?

Score	Meaning
1-2	6+ weeks, requires new infrastructure or external dependency
3-4	4-6 weeks, significant engineering but within our stack
5-6	2-4 weeks, moderate effort, well-understood domain
7-8	1-2 weeks, straightforward implementation
9-10	Days, config change or minor code update

Template

# ICE Scorecard: [Context / Sprint / Quarter]

Date: [YYYY-MM-DD]
Scored by: [Name(s)]

| # | Item | Impact | Confidence | Ease | ICE Score | Rank |
|---|------|--------|------------|------|-----------|------|
| 1 | [Item A] | /10 | /10 | /10 | | |
| 2 | [Item B] | /10 | /10 | /10 | | |
| 3 | [Item C] | /10 | /10 | /10 | | |
| 4 | [Item D] | /10 | /10 | /10 | | |
| 5 | [Item E] | /10 | /10 | /10 | | |

**ICE Score = Impact x Confidence x Ease** (max 1000)

## Scoring Rationale

### [Item A] -- ICE: [score]
- Impact [X]: [why]
- Confidence [X]: [why]
- Ease [X]: [why]

### [Item B] -- ICE: [score]
- Impact [X]: [why]
- Confidence [X]: [why]
- Ease [X]: [why]

[... repeat for each item ...]

## Decision
Top 3 items for this cycle:
1. [Item] -- Owner: [name], Deadline: [date]
2. [Item] -- Owner: [name], Deadline: [date]
3. [Item] -- Owner: [name], Deadline: [date]

Deferred to next cycle: [items and brief reason]

Calibration Notes

Customize these to your company's context:

• Activation metric improvements (e.g., Time to First Hello World < 30 min) score Impact 8+ automatically
• Anything that unblocks a pipeline deal scores Impact 7+ (revenue is existential at early stage)
• Integrations with proven providers have Confidence 7+ because the product already exists
• New product verticals start at Confidence 4-5 until first client validates demand
• Graduate to RICE (add Reach) when you have 50+ clients and need to weight by audience size

---

4. Opportunity Solution Tree (Discovery)

Use when you know the outcome you want but not yet what to build. Based on Teresa Torres' Continuous Discovery framework.

When to Use

• Exploring a problem space before committing (you have a target outcome but multiple paths)
• Synthesizing interview data into actionable opportunities

Template

# Opportunity Solution Tree: [Desired Outcome]

## Target Outcome
[Specific, measurable outcome we are trying to achieve]
- Metric: [what we measure]
- Current: [baseline]
- Target: [goal]
- Timeframe: [by when]

## Opportunity Map
(Repeat this block for each opportunity identified -- aim for 3-5)

### Opportunity N: [Problem/need identified from research]
Evidence: [interview quotes, data points, observation notes]
Frequency: [how often this comes up in research]

  - Solution Na: [possible solution]
    - Experiment: [how to test cheaply]
    - Assumption: [what must be true]
  - Solution Nb: [alternative solution]
    - Experiment: [how to test cheaply]
    - Assumption: [what must be true]

## Interview Synthesis
| Interviewee | Role | Key Quote | Opportunities Mentioned |
|-------------|------|-----------|------------------------|
| [Name/Code] | [Role] | "[quote]" | Opp 1, Opp 3 |
| [Name/Code] | [Role] | "[quote]" | Opp 1, Opp 2 |
| [Name/Code] | [Role] | "[quote]" | Opp 2, Opp 3 |

## Test Plan
| Experiment | Tests Assumption | Method | Success Criteria | Duration |
|------------|-----------------|--------|------------------|----------|
| [Exp 1] | [assumption] | [method] | [criteria] | [time] |
| [Exp 2] | [assumption] | [method] | [criteria] | [time] |
| [Exp 3] | [assumption] | [method] | [criteria] | [time] |

## Next Steps
- [ ] Run experiment [X] this week
- [ ] Interview [N] more [segment] users
- [ ] Reconvene on [date] to update tree

Discovery Focus Areas

Customize these to your company. Common focus areas for platform/API companies:

• Developer onboarding friction: Where do developers get stuck in the first 30 minutes?
• Multi-product adoption: What drives a client from 1 product to 2+ products?
• Provider reliability: Which integrations cause the most support tickets?
• Compliance burden: Where does onboarding create the most friction for clients?

---

5. API Product Spec

Use when designing or extending your API surface. Combines developer job stories with Stripe-inspired design principles.

When to Use

• Adding a new endpoint, modifying behavior, or designing webhooks
• Any change to the developer-facing API surface

Template

# API Product Spec: [Feature / Endpoint]

## Developer Job Story
"When I [situation/context], I want to [action/capability], so I can [outcome/benefit]."

## API Surface Design
| Method | Path | Description |
|--------|------|-------------|
| [GET/POST/...] | /v1/[resource] | [what it does] |

Request body: [JSON schema or example]
Response body: [JSON schema or example]
Error responses: [status codes, error codes, developer actions]
Webhook events (if any): [event names, triggers, payload summaries]

## Consistency Check
- [ ] Naming follows existing /v1/ conventions
- [ ] Pagination, error format, and auth match existing patterns
- [ ] Idempotency key supported on mutating operations
- [ ] Works identically in test mode and production

## Breaking Change Assessment
- [ ] No breaking change (additive only)
- [ ] Minor (new required field with sensible default)
- [ ] Major (requires migration plan, 6-month deprecation, communication plan)

## Test Mode Specification
- Sandbox behavior description
- Test data returned and test-specific parameters

---

Decision Resolutions

These decisions were made during framework selection and should be treated as settled:

Decision	Resolution	Rationale
ICE vs RICE	ICE is primary. Graduate to RICE at 50+ clients.	ICE is simpler. RICE's "Reach" dimension only matters with a large user base.
Kano Model	Future-state only. Not included as active framework.	Kano requires surveying an existing user base. Not useful pre-product-market-fit.
Story Mapping (Jeff Patton)	Optional workflow for B2C MVP definition only.	Useful if/when you explore a B2C consumer app. Not relevant for B2B API.

---

Delegation Guide

When delegating product work to a Claude agent or team member:

Task	Delegate With	Key Instruction
"Write a feature spec"	Shape Up Pitch template	"Fill in Problem and Appetite first. Do NOT skip Non-Goals or Rabbit Holes."
"Evaluate whether we should do X"	DIBB + PR/FAQ template	"Start with Data. If you cannot fill Data with facts, the bet is not ready."
"Rank these items"	ICE Scorecard template	"Score independently first, then calibrate together. Document rationale for every score."
"Explore this problem space"	Opportunity Solution Tree	"Interview at least 3 people before proposing solutions. No solutions without evidence."
"Design this API endpoint"	API Product Spec template	"Run the Consistency Check and Breaking Change Assessment before review."

---

Product Principles

Customize these to your company. Examples for API-first platform companies:

1. API-first, always. Every product decision must answer: "How does this look to a developer integrating our API?" If the answer is unclear, the feature is not shaped.

2. Multi-product is the moat. Single-product features are table stakes. Prioritize work that makes the multi-product experience seamless (unified account, cross-product views, single settlement).

3. Provider-agnostic by design. Never expose provider-specific concepts in the API surface. A client buys "[Product A]" from your platform, not "[underlying asset from Provider A]." Provider switching must be invisible.

4. Uptime is a feature. Design every feature to operate continuously or explicitly document availability constraints.

5. Compliance as a product. Onboarding and compliance are not a tax on the developer experience -- they are product features. Make compliance self-serve, transparent, and fast.

---

Reference Links

Frameworks: Shape Up | DIBB | Continuous Discovery | Stripe API Design