Moat Building

Moat Building

Identity

You are a strategist who has studied why some companies maintain dominance for decades while others get commoditized in years. You've internalized Hamilton Helmer's "7 Powers," analyzed network effects with the NFX team, and understand that moats aren't about being "better" - they're about structural advantages that make competition asymmetric.

You're allergic to founders calling their "great product" a moat. You know that most startups don't have moats and many never will - and that's okay for some businesses. But you also know that the greatest companies in history all had deep moats, and understanding moat dynamics is essential for building lasting businesses.

Principles

• A great product is not a moat - it's a starting point
• The best moats compound over time - they get stronger, not weaker
• Moats protect margins, not just market share
• If you can't articulate your moat, you probably don't have one
• Some businesses are structurally incapable of moats - know which
• Network effects are the strongest moat, but hardest to build

Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

• For Creation: Always consult `references/patterns.md`. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.
• For Diagnosis: Always consult `references/sharp_edges.md`. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
• For Review: Always consult `references/validations.md`. This contains the strict rules and constraints. Use it to validate user inputs objectively.

Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

Moat Building

Patterns

---

Name

The Seven Powers Framework

Description

Hamilton Helmer's framework for sustainable competitive advantages

When

Analyzing or building defensibility

Example

THE SEVEN POWERS:

1. Network Effects

""" VALUE OF PRODUCT INCREASES WITH USERS

Types:

• Direct: More users = more value (WhatsApp)
• Indirect/Platform: More of A = more of B (iOS developers/users)
• Data: More usage = better product (Google Search)
• Social: Value from connections (LinkedIn)

Strength: Extremely strong when present Timing: Must be designed from start Example: Facebook, Uber, Airbnb """

2. Switching Costs

""" LEAVING IS PAINFUL

Types:

• Financial: Exit fees, lost investment
• Procedural: Learning curve, workflow change
• Relational: Relationships built on platform
• Data: History, content, integrations

Strength: Moderate to strong Timing: Builds over customer lifetime Example: Salesforce, SAP, Adobe Creative Suite """

3. Scale Economies

""" BIGGER = CHEAPER PER UNIT

How:

• Fixed costs spread over more units
• Purchasing power with suppliers
• R&D amortization
• Operational efficiency

Strength: Moderate, but vulnerable to disruption Timing: Takes time to achieve scale Example: Amazon, Costco, TSMC """

4. Brand

""" CUSTOMERS PAY MORE FOR THE NAME

Components:

• Trust and reliability signal
• Status and identity
• Reduced search costs
• Quality guarantee

Strength: Strong in consumer, less in B2B Timing: Years to build Example: Apple, Nike, Tiffany """

5. Cornered Resource

""" ACCESS TO SOMETHING OTHERS CAN'T GET

Types:

• Patents and IP
• Exclusive contracts
• Unique talent
• Proprietary data
• Geographic rights

Strength: Strong but often temporary Timing: Often luck or early mover Example: DeBeers (diamonds), Qualcomm (patents) """

6. Counter-Positioning

""" NEW MODEL INCUMBENTS CAN'T COPY

Why it works:

• Copying would damage incumbent's business
• Cannibalization fear
• Organizational inertia

Strength: Strong until incumbents adapt Timing: Early-stage advantage Example: Netflix vs Blockbuster, Vanguard vs active funds """

7. Process Power

""" EMBEDDED ORGANIZATIONAL KNOW-HOW

How:

• Complex processes honed over time
• Organizational culture and practices
• Tacit knowledge that can't be copied

Strength: Strong but takes years Timing: Long-term development Example: Toyota Production System, Pixar creative process """

---

Name

Network Effects Deep Dive

Description

Understanding and building network effects

When

Evaluating or designing for network effects

Example

NETWORK EFFECTS IN DEPTH:

Direct Network Effects

""" More users = more valuable for each user

EXAMPLES:

• Phone network (who can I call?)
• WhatsApp (who can I message?)
• Multiplayer games (who can I play with?)

BUILDING STRATEGY:

• Solve chicken-and-egg with single-player value
• Seed both sides (subsidize one)
• Geographic concentration first
• Critical mass threshold varies

"""

Two-Sided/Platform Network Effects

""" More of side A = more value for side B (and vice versa)

EXAMPLES:

• iOS: More developers → more users → more developers
• Uber: More drivers → more riders → more drivers
• YouTube: More creators → more viewers → more creators

BUILDING STRATEGY:

• Subsidize the harder side to acquire
• Create single-side value first
• Manage chicken-and-egg carefully
• Winner often takes most (but not all)

"""

Data Network Effects

""" More usage = better product = more usage

EXAMPLES:

• Google: More searches → better results → more searches
• Waze: More drivers → better traffic → more drivers
• Netflix: More watching → better recommendations → more watching

BUILDING STRATEGY:

• Design for data collection from day one
• Build ML/AI that improves with data
• Data must create visible value improvement
• Beware: Diminishing returns at scale

"""

Social/Tribal Network Effects

""" Value from being part of the community

EXAMPLES:

• LinkedIn: Professional identity and network
• GitHub: Developer reputation and profile
• Strava: Athlete community and status

BUILDING STRATEGY:

• Create portable identity and reputation
• Enable status signaling
• Build community rituals and norms
• Make leaving = losing social capital

"""

NETWORK EFFECT MATH:

""" Metcalfe's Law: Value = n² (connections between n users) Reality is usually: Value = n × log(n) (diminishing returns)

Key question: At what n does network become valuable?

• Some products useful at n=2 (messaging)
• Some need n=1000s (marketplace)
• Some need n=millions (social network)

"""

---

Name

Switching Cost Engineering

Description

Designing products that are hard to leave

When

Building retention and defensibility

Example

SWITCHING COST DESIGN:

Data Lock-in

""" Customer's data becomes trapped in your system

TACTICS:

• Store customer's work product (Notion docs, Figma files)
• Accumulate history (Slack messages, email)
• Build integrations (connected to everything)
• Custom configurations (settings, workflows)

MAKE EXPORT POSSIBLE BUT PAINFUL:

• Offer data export (ethics + trust)
• But exported data loses structure, context
• Importing elsewhere requires rebuilding

"""

Integration Lock-in

""" Customer integrates deeply with your system

TACTICS:

• API integrations with their stack
• Single sign-on and identity
• Workflow automations
• Third-party app ecosystem

RESULT: Switching = rewiring their entire tech stack """

Learning Curve Lock-in

""" Customer has invested in learning your system

TACTICS:

• Unique interface (learn once, use forever)
• Power user features (expertise compounds)
• Certifications and training
• Team knowledge base built on your product

RESULT: Switching = retraining entire team """

Relationship Lock-in

""" Human relationships built around your product

TACTICS:

• Dedicated customer success
• Community and peer connections
• Partnerships and ecosystem
• Shared history and trust

RESULT: Switching = leaving relationships behind """

Contract Lock-in

""" Explicit commitment to stay

TACTICS:

• Annual or multi-year contracts
• Volume commitments
• Preferred pricing for loyalty
• Penalty for early termination

RESULT: Switching = financial penalty """

ETHICAL SWITCHING COSTS:

""" Good switching costs: Created from genuine value

• Data you've helped them create
• Expertise they've developed
• Integrations they chose

Bad switching costs: Artificial barriers

• Hidden export fees
• Proprietary formats
• Deliberately crippled exports

Rule: Switching should be hard because value is deep, not because you've trapped them. """

---

Name

Moat Assessment Framework

Description

Evaluating moat strength for any company

When

Analyzing competitive position

Example

MOAT ASSESSMENT:

The Moat Strength Test

Question 1: Pricing Power

""" "Can you raise prices 10% without losing customers?"

YES → You have some moat NO → Commodity or weak position

Strong moat = significant pricing power No moat = race to zero margin """

Question 2: Time to Copy

""" "If a competitor with $10M started today, how long to match you?"

< 1 year → No moat 1-3 years → Weak moat 3-5 years → Moderate moat 5+ years → Strong moat Never (structural) → Very strong moat """

Question 3: Moat Direction

""" "Is your advantage getting stronger or weaker over time?"

Stronger (network effects, data) → Compounding moat Stable (brand, contracts) → Maintainable moat Weaker (patents expiring, tech commoditizing) → Eroding moat """

Question 4: Moat Width

""" "How big is the cost/effort for a customer to switch?"

Trivial (download competitor app) → No moat Annoying (migrate data, retrain) → Narrow moat Significant (rewire integrations) → Medium moat Prohibitive (organizational change) → Wide moat """

Moat Scoring Matrix

Score 0-2: No moat yet Score 3-5: Emerging moat Score 6-8: Solid moat Score 9-10: Deep moat

---

Name

Building Moat Over Time

Description

When and how moats can be built at each stage

When

Planning long-term defensibility

Example

MOAT BUILDING TIMELINE:

Pre-PMF: Counter-Positioning

""" Your best moat is a model incumbents can't copy.

EXAMPLES:

• Direct-to-consumer vs retail
• Subscription vs one-time
• Self-serve vs sales-led
• Open source vs proprietary

This buys you time while you build real moats. """

Early Growth: Network Effects Seeds

""" Design for network effects even if they don't exist yet.

TACTICS:

• Make sharing core to product
• Build multi-player features early
• Collect data that will power ML later
• Create community from first users

Network effects don't appear - they're designed. """

Growth Phase: Switching Costs

""" Every month of usage should increase lock-in.

TACTICS:

• Data accumulation (history, content)
• Integration expansion
• Power user features
• Team adoption and training

Customer using you for 2 years should be 10x harder to churn. """

Scale Phase: Scale Economies + Brand

""" Size enables advantages others can't match.

TACTICS:

• Spread fixed costs across volume
• Negotiate supplier leverage
• Invest in brand with profits
• Build process power

At scale, your costs per user should beat competitors. """

Maturity: Multiple Moats

""" The strongest companies stack moats.

AMAZON STACK:

• Scale (logistics, purchasing)
• Network (marketplace sellers/buyers)
• Data (recommendation, search)
• Brand (trust)
• Switching (Prime, integrations)

One moat can be breached. Multiple moats = fortress. """

Anti-Patterns

---

Name

"Great Product" as Moat

Description

Believing product quality alone is defensible

Why

Products can be copied. Features can be matched. If you're competing on product alone, you're in an arms race. Eventually someone with more resources catches up. Great product is necessary but not sufficient.

Instead

Great product + structural advantage. Product creates value, moat protects it.

---

Name

First Mover Illusion

Description

Believing being first creates lasting advantage

Why

First mover rarely wins unless they also build a moat. MySpace was first. Friendster was first. Yahoo was first. Being first just means you do the market education for the winner who follows.

Instead

First mover advantage only matters if you use the time to build moats.

---

Name

Moat Confusion

Description

Mistaking temporary advantages for moats

Why

VC funding is not a moat. Exclusive partnership is not a moat (until contract ends). Being in hot space is not a moat. Founder expertise is not a moat (can be hired away). Real moats are structural.

Instead

Ask "will this advantage compound or erode over time?"

---

Name

Premature Moat Focus

Description

Worrying about moat before product-market fit

Why

Moats protect valuable businesses. Before PMF, you don't have a valuable business to protect. Focusing on moat before value is putting cart before horse. Get to value first.

Instead

Find PMF first. Then build moat. Moat without value protects nothing.

---

Name

Single Moat Reliance

Description

Depending on one source of competitive advantage

Why

Any single moat can be breached. Technology changes. Regulations change. Competitors innovate. Companies that rely on one moat are vulnerable. The greatest companies stack multiple moats.

Instead

Build primary moat, then layer additional moats over time.

---

Name

Ignoring Moat Erosion

Description

Not monitoring and maintaining competitive advantages

Why

Moats erode. Patents expire. Technology commoditizes. Network effects can be overcome with better product. Scale can be matched. Continuous investment in moat maintenance is required.

Instead

Regularly assess moat strength. Invest in deepening. Add new moats.

---

Name

Copying Competitor Moats

Description

Trying to build same moat as incumbent

Why

If incumbent has network effects, you can't just build network effects. They're ahead. You need a different moat or a wedge strategy. Don't fight battles on their terrain.

Instead

Find orthogonal moat or wedge into market where their moat doesn't apply.

Moat Building - Sharp Edges

Fake Network Effects - Virality ≠ Network Effects

Id

fake-network-effects

Severity

high

Situation

Founder pitches: "We have network effects. Users share content and invite friends." Growth is viral. Deck shows hockey stick. But when growth slows, retention craters. Users leave as easily as they came. There was virality, not network effects.

Why

Virality is about spreading. Network effects are about stickiness. Virality gets users in the door. Network effects keep them there. A product can be viral without network effects (viral videos) or have network effects without virality (enterprise software).

Solution

1. The network effect test:

• Does the product get MORE valuable as users increase?
• Would a user who left lose significant value?
• Is there lock-in from the network itself?

2. Virality vs network effects: """ VIRAL ONLY: User shares → Friend joins → Repeat

• Value to sharer: Same
• Value to friend: Independent
• Switching cost: None

NETWORK EFFECTS: User joins → Value increases → More join

• Value to all users: Increases with size
• Switching cost: Lose the network

"""

3. Build network effects ON viral growth:

• Viral gets them in
• Network effects keep them
• Design for both, separately

Symptoms

• High growth but high churn
• Users join but don't connect
• Single-player usage patterns
• "Viral" in pitch but no lock-in

Detection Pattern

viral|network effects|sharing|invite

Data Moat Delusion - Data Alone Isn't a Moat

Id

data-moat-delusion

Severity

high

Situation

Startup has lots of data. Investor asks about moat. Founder says "data is our moat." But the data isn't proprietary. It's scraped, or public, or easily replicated by competitors with money. Two years later, well- funded competitor has same data and better product.

Why

Data is only a moat when it's (1) proprietary - you have it and others can't get it, (2) compounding - more usage = more data = better product, and (3) defensible - the data advantage is hard to replicate even with resources. Most "data moats" fail all three tests.

Solution

1. Data moat requirements: """ PROPRIETARY: ✓ Users create unique data in your product ✗ Data from public sources ✗ Data that can be scraped/bought

COMPOUNDING: ✓ More usage → better product ✗ Data sits unused ✗ Improvement is linear, not exponential

DEFENSIBLE: ✓ Years of accumulation needed ✗ Can be replicated with $10M ✗ Cold start works fine """

2. Data moat examples:

• Google: Decades of search behavior
• Waze: Real-time traffic from active users
• Netflix: Viewing patterns for recommendations

3. NOT data moats:

• Scraped web data (anyone can do it)
• Purchased datasets (available to competitors)
• Public APIs (same access for all)

Symptoms

• "Data is our moat" with no proprietary data
• Data could be bought or scraped
• Competitors catching up on data quickly

Detection Pattern

data moat|data advantage|proprietary data

Marketplace Cold Start Underestimate - Chicken-Egg Is Brutal

Id

marketplace-cold-start-underestimate

Severity

critical

Situation

Marketplace idea: Connect X with Y. Build the platform. Launch. Buyers want sellers. Sellers want buyers. Neither will come first. Growth stalls. Team spends 18 months solving cold start. Runway depleting. Competitors who started in niche are now scaling.

Why

Marketplaces have the strongest network effects when working, but the hardest cold start problem. You need both sides to have value. Getting the first side with no other side is incredibly hard. Most marketplace attempts fail at this stage.

Solution

1. Cold start strategies: """ SINGLE-PLAYER VALUE:

• Make one side useful without other side
• OpenTable: Reservation system for restaurants (no diners needed)
• Then add the other side

SUBSIDIZE ONE SIDE:

• Pay or incentivize the hard side
• Uber: Guaranteed hourly for drivers
• Creates supply, demand follows

CONSTRAIN MARKET:

• Launch in tiny market where you can "fill" both sides
• Uber: San Francisco only
• Airbnb: Conferences where hotels sold out

HYBRID MODEL:

• Be one side yourself initially
• Amazon: First-party before marketplace
• Own inventory until third-party takes over

PRE-AGGREGATE SUPPLY:

• Scrape or list supply without consent
• Yelp: Listed restaurants before they knew
• Create demand-side value first

"""

2. Marketplace readiness test:

• Do you have a cold start strategy?
• How will you get first 100 of each side?
• What's the minimum viable liquidity?

Symptoms

• Building platform before solving cold start
• "If we build it, they will come"
• Both sides waiting for other

Detection Pattern

marketplace|two-sided|platform|buyers.*sellers

Switching Cost Overestimate - Customers Can Leave Easier Than You Think

Id

switching-cost-overestimate

Severity

medium

Situation

Company believes customers are locked in. High switching costs. Years of data. Deep integrations. Then competitor launches with better product and easy migration. Customers switch in weeks. The "lock-in" wasn't as strong as assumed.

Why

Companies overestimate their switching costs because they don't understand customer motivation. Customers put up with switching pain when new product is significantly better or current one is causing significant pain. Switching costs are speed bumps, not walls.

Solution

1. Switching cost reality check: """ YOUR VIEW: "Years of data, complex integrations, team trained" CUSTOMER VIEW: "This isn't working, we'll figure it out"

Switching costs delay switching. They don't prevent it if motivation is high enough. """

2. Switching cost strength varies by:

• Pain with current solution (higher = more likely to switch)
• Value of new solution (higher = more likely to switch)
• Actual switching effort (lower than you think)
• Competitive migration tools (getting easier)

3. Don't rely on switching costs alone:

• Lock-in from value > lock-in from friction
• If customers stay only because leaving is hard, they're unhappy
• Unhappy captive customers are time bombs

Symptoms

• Relying on lock-in instead of value
• High switching costs but customers still churning
• Competitors offering migration tools

Detection Pattern

switching costs|lock-in|churn|migration

Brand Moat Takes Decades - You Can't Shortcut Brand

Id

brand-moat-takes-decades

Severity

medium

Situation

Startup wants brand moat. Spends heavily on marketing, PR, influencers. High awareness achieved. But when price-checking, customers still go with cheaper option. Brand awareness exists, but brand moat doesn't. Years of spend, no pricing power.

Why

Brand awareness is not brand moat. Brand moat means customers pay premium for your brand alone. This requires years of consistent quality, trust-building, and emotional connection. It can't be bought with marketing spend. It's earned over decades.

Solution

1. Brand awareness vs brand moat: """ AWARENESS: "I know who you are" MOAT: "I'll pay 30% more for your name"

Awareness is table stakes. Moat is pricing power. """

2. Brand moat timeline:

• Years 1-3: Building reputation
• Years 3-7: Establishing trust
• Years 7-15: Creating emotional connection
• Years 15+: True brand moat

3. Brand moat requirements:

• Consistent quality over time
• Category leadership
• Emotional resonance
• Status signaling

4. Startups should focus on:

• Other moats (network, switching) first
• Brand as long-term investment
• Product quality as brand foundation

Symptoms

• High awareness but no pricing power
• Heavy marketing spend but commodity perception
• "We'll build a brand" as strategy

Detection Pattern

brand|awareness|marketing spend|premium

Scale Without Advantage - Big Isn't Automatically Better

Id

scale-without-advantage

Severity

medium

Situation

Company achieves scale. Large customer base. High revenue. But margins are still thin. Competitors with less scale have similar economics. The scale didn't create advantage. They're just a big commodity business.

Why

Scale is only a moat when it creates structural cost advantage or unique capabilities. Pure volume without efficiency gains is just... bigger. Many businesses have no scale economies - they're linear, not exponential.

Solution

1. Scale economy requirements: """ WORKS:

• High fixed costs spread over units (software, R&D)
• Purchasing power with volume (retail, manufacturing)
• Operational efficiency from learning (logistics)

DOESN'T WORK:

• Service businesses (linear cost per customer)
• Low fixed cost businesses
• Businesses with local competition

"""

2. Test for scale advantage:

• "Are my margins improving with scale?"
• "Is my cost per unit decreasing?"
• "Can competitors match my economics at smaller scale?"

3. If scale doesn't help:

• Don't pursue scale for its own sake
• Focus on other moats
• Or accept you're in a commodity business

Symptoms

• Large but low-margin
• Competitors profitable at smaller scale
• No cost per unit improvement

Detection Pattern

scale|volume|size|growth

Moat Before Value - Protecting Nothing

Id

moat-before-value

Severity

high

Situation

Founder obsessed with defensibility. Every decision filtered through "is this a moat?" Patents filed. Proprietary formats created. Lock-in designed. But nobody wants the product. The moat protects a castle nobody wants to live in.

Why

Moats protect valuable businesses. Before product-market fit, you don't have a valuable business to protect. Focusing on moat before value is premature optimization. You're building walls around an empty lot.

Solution

1. Sequence matters: """ CORRECT ORDER: 1. Find product-market fit 2. Prove value creation 3. Build moat to protect value 4. Deepen moat over time

WRONG ORDER: 1. Design moat 2. Build product with moat 3. Hope customers want it """

2. Pre-PMF moat thinking:

• Counter-positioning (model incumbents can't copy)
• Seeds for future network effects
• But NOT: Heavy lock-in, proprietary everything

3. When to focus on moat:

• Retention is strong (40%+ D30)
• Clear PMF signals
• Growth is accelerating
• Competitors are emerging

Symptoms

• Moat discussions before PMF
• Features designed for lock-in, not value
• Defensive patents but no customers

Detection Pattern

defensibility|protect|moat|too early

Single Moat Vulnerability - One Point of Failure

Id

single-moat-vulnerability

Severity

medium

Situation

Company has one moat: a key patent. Patent expires in 2 years. Competitor is already developing similar product. When patent expires, so does the moat. Company is suddenly in commodity market with no other advantage.

Why

Every moat has vulnerabilities. Patents expire. Network effects can be overcome with better product. Scale can be matched. Regulations change. Companies relying on single moat are fragile to any attack on that moat.

Solution

1. Moat stacking: """ AMAZON MOAT STACK:

• Scale (logistics infrastructure)
• Network (marketplace)
• Data (customer behavior)
• Switching (Prime membership)
• Brand (trust)

One moat breached? Four others still standing. """

2. Moat diversification timeline:

• Years 1-3: Primary moat (often counter-positioning)
• Years 3-5: Add switching costs
• Years 5-10: Add scale, data, brand
• Years 10+: Multiple reinforcing moats

3. Moat health monitoring:

• Which moat is strongest?
• Which is most vulnerable?
• What are we doing to add moats?

Symptoms

• All defensibility from one source
• That source is time-limited or fragile
• No moat diversification plan

Detection Pattern

patent|single.moat|only.advantage

Network Effects Wrong Direction - Negative Network Effects

Id

network-effects-wrong-direction

Severity

high

Situation

Platform grows. More users join. But experience degrades. Spam increases. Quality drops. Original users leave. New users find poor experience. Growth stalls. The network effects turned negative.

Why

Network effects can be positive or negative. More users can mean more spam (email, Twitter), more noise (forums), worse matching (dating apps at scale), or lower quality (user-generated content platforms). Without curation, networks can eat themselves.

Solution

1. Negative network effect triggers: """

• Spam and bad actors (email, social)
• Noise drowning signal (forums, feeds)
• Reduced matching quality (dating, marketplaces)
• Quality dilution (UGC platforms)
• Congestion (two-sided platforms)

"""

2. Prevention mechanisms:

• Curation and moderation (human or algorithmic)
• Reputation systems (seller ratings, karma)
• Community standards enforcement
• Segmentation (subreddits, groups)
• Density over breadth (local focus)

3. Quality metrics alongside growth:

• Track engagement quality, not just volume
• Monitor spam/noise ratios
• Watch for early user exodus
• Measure NPS alongside MAU

Symptoms

• Quality declining with growth
• Early users leaving
• Spam or noise increasing
• Engagement metrics flat despite user growth

Detection Pattern

spam|quality|noise|community|moderation

Moat Building - Validations

Social Feature Without Sharing

Id

missing-viral-hooks

Severity

info

Type

regex

Pattern

• social|Social|community|Community
• collaboration|Collaboration
• team|Team|workspace

Message

Social/collaborative feature found. Consider adding sharing and invite mechanics.

Fix Action

Add invite flows, sharing buttons, and viral loops to collaborative features

Applies To

• */.tsx
• */.jsx

Exceptions

• share|Share|invite|Invite|referral

User Action Without Data Capture

Id

no-data-persistence

Severity

info

Type

regex

Pattern

• onClick|onSubmit|handleClick
• user.*action

Message

User action handler without visible analytics/data capture.

Fix Action

Ensure valuable user actions are logged for future ML/personalization

Applies To

• */.tsx
• */.jsx

Exceptions

• track|log|analytics|capture

Proprietary Format Without Export

Id

exportable-data-format

Severity

warning

Type

regex

Pattern

• proprietary.*format
• custom.*format
• \.myapp|\.internal

Message

Proprietary format detected. Ensure ethical export option exists.

Fix Action

Provide standard format export (CSV, JSON, etc.) alongside proprietary

Applies To

• */.ts
• */.tsx
• */.js

Product Without Integration Points

Id

no-integration-api

Severity

info

Type

regex

Pattern

• export default.*App
• createRoot|render\(

Message

Main app without visible API/integration layer. Consider for switching costs.

Fix Action

Add webhook, API, or integration capabilities for deeper customer embedding

Applies To

• **/App.tsx
• **/index.tsx
• **/main.tsx

Exceptions

• api|API|webhook|integration

Single-User Focus Without Team Features

Id

single-user-only

Severity

info

Type

regex

Pattern

• user\s*=|currentUser|getUser

Message

Single-user patterns found. Consider team/org features for network effects.

Fix Action

Plan team features: shared workspaces, permissions, collaboration

Applies To

• */.ts
• */.tsx

Exceptions

• team|org|organization|member|workspace

User Signup Without Referral Tracking

Id

no-referral-system

Severity

info

Type

regex

Pattern

• signup|signUp|register|createUser

Message

User signup without referral tracking. Missing viral loop opportunity.

Fix Action

Add referral code tracking and attribution for viral growth

Applies To

• */.ts
• */.tsx

Exceptions

• referral|refer|invite|attribution

Feature Without Usage History

Id

no-usage-history

Severity

info

Type

regex

Pattern

• save|Save|create|Create|submit|Submit

Message

Create/save action without history accumulation.

Fix Action

Store user history/activity for personalization and switching cost depth

Applies To

• */.ts
• */.tsx

Exceptions

• history|log|activity|audit

Content Display Without Personalization

Id

no-personalization

Severity

info

Type

regex

Pattern

• getAll|findAll|listAll
• fetch.*all

Message

Generic content fetch without personalization. Data moat opportunity.

Fix Action

Add user preference/behavior-based personalization for data network effects

Applies To

• */.ts
• */.tsx

Exceptions

• recommend|personalize|preference|score

Core Feature Without Extension Points

Id

missing-platform-hooks

Severity

info

Type

regex

Pattern

• export.function|export.const
• class.*export

Message

Core functionality without extension points. Platform moat opportunity.

Fix Action

Consider plugin architecture, webhooks, or API for platform network effects

Applies To

• /core//*.ts
• /lib//*.ts

Exceptions

• plugin|hook|extension|middleware

Standard Format Without Lock-in

Id

easy-migration-pattern

Severity

info

Type

regex

Pattern

• import.csv|export.csv
• import.json|export.json
• standard.*format

Message

Standard format usage. Good for ethics, consider proprietary value-add layer.

Fix Action

Balance: Standard format export + proprietary features/integrations

Applies To

• */.ts
• */.tsx

User-Generated Content Without Community

Id

no-community-features

Severity

info

Type

regex

Pattern

• upload|post|publish|share
• content.*create

Message

User content creation without community features.

Fix Action

Add comments, likes, follows, or reputation for social network effects

Applies To

• */.tsx
• */.jsx

Exceptions

• comment|like|follow|community|social

Utility Without Workflow Integration

Id

no-embedded-workflows

Severity

info

Type

regex

Pattern

• utility|tool|helper
• standalone.*app

Message

Standalone utility pattern. Consider workflow embedding for switching costs.

Fix Action

Integrate into customer workflows via integrations, plugins, or APIs

Applies To

• */.ts
• */.tsx

Exceptions

• workflow|integrate|embed|plugin

Feature Launch Without Competitive Context

Id

competitive-analysis-missing

Severity

info

Type

regex

Pattern

• launchFeature|releaseFeature|newFeature
• feature.*flag

Message

Feature launch detected. Ensure competitive moat assessment.

Fix Action

Document how this feature affects competitive positioning and moat strength

Applies To

• */.ts
• */.tsx
• */feature