Wedge Generator

Required

1. Validated Signal Data (from signal-detector)

   • Signal Type (Trust / Intent)
   • Signal Subtype (e.g., Fragmentation Pain, Community Engagement)
   • Signal text (raw observed behavior)
   • Prospect ICP

2. Monthly Theme (from campaign-strategist)

   • One-line monthly wedge theme
   • Example: "Data Fragmentation Crisis"

3. Weekly Wedge Strategy (from campaign-strategist)

   • Different angles (A - default)
   • Sequential story (B)
   • A/B/C variants (C)

4. ICP Context

   • MENA SaaS Founders / US Real Estate Brokers / MENA Beauty Clinics / US eCommerce

Optional

• Performance data (if Mode B - wedge refinement)
• Existing wedges (if creating A/B variants)
• Geographic market (for Culture Map adaptation)

Outputs

3 Weekly Wedges (Validated)

## Weekly Wedges - [Campaign Name]

### Week 1 Wedge
**Wedge**: "[One-sentence wedge]"
**Signal Source**: [Intent/Trust: Subtype]
**ICP**: [Target ICP]
**Angle**: [Identify problem / Amplify pain / Provide solution / etc.]
**Validation**:
  - One-sentence test: ✓ PASS
  - No hedging: ✓ PASS
  - Specific (not vague): ✓ PASS
  - ICP resonance: ✓ PASS

### Week 2 Wedge
**Wedge**: "[One-sentence wedge]"
**Signal Source**: [Intent/Trust: Subtype]
**ICP**: [Target ICP]
**Angle**: [Different from Week 1]
**Validation**:
  - One-sentence test: ✓ PASS
  - No hedging: ✓ PASS
  - Specific (not vague): ✓ PASS
  - ICP resonance: ✓ PASS

### Week 3 Wedge
**Wedge**: "[One-sentence wedge]"
**Signal Source**: [Intent/Trust: Subtype]
**ICP**: [Target ICP]
**Angle**: [Different from Week 1 and 2]
**Validation**:
  - One-sentence test: ✓ PASS
  - No hedging: ✓ PASS
  - Specific (not vague): ✓ PASS
  - ICP resonance: ✓ PASS

## Hard Stop Rules Applied
- Rule 3 (One-sentence test): ✓ All wedges pass
- Rule 4 (Intent > Trust): ✓ Applied where both present

Wedge Creation Logic

Core Formula (from wedge-sentence-map.md)

[Observed Signal] is costing you [Specific Outcome]. [One-Line Solution].

Variations:

• Problem-focused: "[Signal] is creating [Pain]. [Solution] is the fix."
• Outcome-focused: "[Current State] generates [Low Metric]. [Better State] generates [High Metric]. That's [X]x ROI."
• Proof-focused: "[X Peers] faced [Signal]. After [Solution], they achieved [Outcome]."

ICP-Specific Templates

MENA SaaS Founders (High-Context, Trust-First)

Pattern 1: Data Fragmentation

Template: "Your [asset] across [X tools] is creating [pain]. [Solution] = [outcome]."

Examples:
- "Your sales data across 7 tools is creating decision paralysis. Unified dashboard = predictable revenue."
- "Pipeline visibility disappeared across HubSpot, Pipedrive, and 4 spreadsheets. One view brings it back."

Pattern 2: Geographic Distribution

Template: "Your [team/asset] is scattered across [cities]. Your [system] isn't. [Regional solution] is the missing piece."

Examples:
- "Your sales team is scattered across Dubai, Riyadh, and Cairo. Your CRM isn't. Regional dashboards are the missing piece."
- "Customers in 5 MENA markets. Support team in one. Regional response system closes the gap."

Pattern 3: Peer Proof

Template: "[X MENA founders] faced [signal]. After [solution], they [outcome]."

Examples:
- "5 MENA SaaS founders unified their scattered stack. They closed 40% more deals."
- "Dubai founders consolidated data across 7 tools. Predictable revenue became possible."

US Real Estate Brokers (Low-Context, Task-First)

Pattern 1: Golden Window (Speed)

Template: "Responding after [X time] costs you [Y]x in conversion. The first [golden window] is everything."

Examples:
- "Responding after 30 minutes costs you 21x in conversion. The first 5 minutes is everything."
- "Your lead fills a form at 2pm. You reply at 5pm. They booked with someone else at 2:07pm."

Pattern 2: Lead Leakage

Template: "[X]% of your leads say '[objection].' [Y]% will [convert] after [touchpoints]. You're missing the [opportunity]."

Examples:
- "98% of your leads say 'I'll think about it.' 80% will book after 5-12 touchpoints. You're missing the backend 50x improvement."
- "Only 2% book immediately. The other 98% need 7 touches over 30 days. That's where the revenue is."

Pattern 3: Listing Capture

Template: "[X people] walked through your open house. [Y captured]. [$Z revenue] lost."

Examples:
- "150 people walked through your open house. 12 captured. $2.1M in potential commission lost."
- "Every showing without capture = invisible buyer. Capture system = warm pipeline."

MENA Beauty Clinics (Visual-First, Trust-Driven)

Pattern 1: Social Follower Leakage

Template: "Instagram [followers/engagement] generate [low $]. [Owned contacts] generate [high $]. That's [X]x ROI."

Examples:
- "Instagram followers generate $79 per 1000. Owned contacts generate $582. That's 8x ROI you're leaving on the table."
- "10k Instagram followers. 127 in your CRM. You own 1.2% of your audience."

Pattern 2: Backend Nurture Gap

Template: "[X]% of clients say '[objection].' [Y]% will book after [touchpoints]. You're missing the backend [outcome]."

Examples:
- "98% of your leads say 'I'll think about it.' 80% will book after 5-12 touchpoints. You're missing the backend 50x improvement."
- "Only 2% book laser treatment on first inquiry. The rest need proof, trust, timing. That's 98% revenue you're not nurturing."

Pattern 3: Response Window

Template: "Someone DMs about [treatment] at [time]. You respond at [later time]. They booked with [competitor] who replied in [minutes]."

Examples:
- "Someone DMs about Botox at 2pm. You respond at 5pm. They booked with a competitor who replied in 5 minutes."
- "WhatsApp inquiry comes in. You're with a patient. Auto-reply captures them. Manual-only loses them."

US eCommerce (DTC) (Data-Driven, Friction-Sensitive)

Pattern 1: Checkout Friction

Template: "[X]% abandon at [checkout step]. [Root cause] is the killer. [Solution] = [Y]% recovery."

Examples:
- "67% abandon at 'Create Account.' Guest checkout + email capture = 43% recovery."
- "Your checkout has 7 steps. Every step costs you 15%. That's 105% cumulative leakage."

Pattern 2: Email List ROI

Template: "[Paid channel] costs [$/acquisition]. [Owned list] costs [$]. That's [X]x difference in LTV."

Examples:
- "Facebook ads cost $47 per customer. Email list nurture costs $6. That's 8x ROI on owned audience."
- "Paid traffic without capture = rent. Email list = ownership. 10x LTV difference."

Pattern 3: Mobile Optimization

Template: "[X]% of traffic is mobile. [Y]% convert. Desktop converts at [Z]%. Mobile friction = revenue leak."

Examples:
- "68% of your traffic is mobile. 2.1% convert. Desktop converts at 8.3%. Mobile checkout friction is costing you $23k monthly."
- "Mobile users don't fill 14-field forms. They abandon. 3-field form = 4x mobile conversion."

Hard Stop Rule 3: One-Sentence Test

Validation Logic

def validate_one_sentence(wedge_text):
    # Test 1: Count sentences
    sentence_count = wedge_text.count('.') + wedge_text.count('!') + wedge_text.count('?')

    if sentence_count > 1:
        return {
            'pass': False,
            'reason': f'Multiple sentences detected ({sentence_count}). Signal too complex.'
        }

    # Test 2: Check for hedging language
    hedging_words = ['might', 'could', 'possibly', 'perhaps', 'maybe', 'potentially']
    if any(word in wedge_text.lower() for word in hedging_words):
        return {
            'pass': False,
            'reason': 'Hedging language detected. Signal lacks conviction.'
        }

    # Test 3: Check for vague language
    vague_terms = ['better results', 'improvement', 'optimization', 'more efficient', 'enhanced']
    if any(term in wedge_text.lower() for term in vague_terms):
        return {
            'pass': False,
            'reason': 'Vague language detected. Signal not specific enough.'
        }

    # Test 4: Check for specificity (numbers, metrics, tangible outcomes)
    has_specificity = any([
        any(char.isdigit() for char in wedge_text),  # Contains numbers
        '$' in wedge_text or '%' in wedge_text,      # Contains metrics
        'x' in wedge_text.lower()                     # Contains multiplier (8x, 21x)
    ])

    if not has_specificity:
        return {
            'pass': False,
            'reason': 'No specific metrics or outcomes. Add data (%, $, Xx).'
        }

    return {
        'pass': True,
        'reason': 'Passes one-sentence test'
    }

Examples: PASS vs FAIL

✓ PASS:

• "Your sales data across 7 tools is creating decision paralysis. Unified dashboard = predictable revenue."
  • One sentence ✓, No hedging ✓, Specific (7 tools) ✓

✗ FAIL: Multiple Sentences:

• "Your sales data is scattered. This causes problems. We can help."
  • Three sentences ✗

✗ FAIL: Hedging:

• "You might be considering CRM alternatives. We could potentially help."
  • Hedging (might, could, potentially) ✗

✗ FAIL: Vague:

• "You want better sales results. We help companies optimize their sales process."
  • Vague ("better results," "optimize") ✗

Hard Stop Rule 4: Intent > Trust

Priority Logic

def apply_intent_priority(signals):
    intent_signals = [s for s in signals if s['type'] == 'Intent']
    trust_signals = [s for s in signals if s['type'] == 'Trust']

    if intent_signals and trust_signals:
        # Both present → Use Intent (Hard Stop Rule 4)
        selected_signal = select_highest_priority(intent_signals)
        log(f"Both Intent and Trust present. Using Intent: {selected_signal}")
        return selected_signal

    elif intent_signals:
        # Only Intent → Use it
        return select_highest_priority(intent_signals)

    elif trust_signals:
        # Only Trust → Use it
        return select_highest_priority(trust_signals)

    else:
        # No signals → Error
        raise ValueError("No signals available for wedge generation")

Example: Intent Overrides Trust

Prospect: MENA SaaS Founder

Trust Signal (20 days ago): "Posted article on LinkedIn: 'The Challenges of Scaling B2B Sales in MENA'"

Intent Signal (5 days ago): "Posted: 'Our sales data lives in HubSpot, Pipedrive, Notion, and 4 Google Sheets. Decision paralysis is real.'"

Application of Rule 4:

Both signals present
Intent signal age: 5 days (fresh)
Trust signal age: 20 days (fresh)

Intent > Trust (Rule 4)
→ Use Intent signal
→ Wedge: "Your sales data across 7 tools is creating decision paralysis. Unified dashboard = predictable revenue."

Why: Intent signal shows ACTIVE PAIN (right now). Trust signal shows thought leadership (passive).

Weekly Wedge Strategy Execution

Strategy A: Different Angles (Default)

Input: Monthly Theme = "Data Fragmentation Crisis"

Output:

• Week 1: "Your sales data lives in 7 different tools. Decision paralysis is costing you deals."
  • Angle: Identify problem (scattered state)
• Week 2: "Scattered data = invisible pipeline. Unified dashboard = predictable revenue."
  • Angle: Amplify cost (visibility loss)
• Week 3: "5 MENA SaaS founders unified their stack. They closed 40% more deals."
  • Angle: Provide proof (peer validation)

Validation: All 3 relate to monthly theme ✓, Each is different angle ✓

Strategy B: Sequential Story

Input: Monthly Theme = "Golden Window Response Speed"

Output:

• Week 1: "Your lead fills a form at 2pm. You reply at 5pm. They booked with someone else at 2:07pm."
  • Chapter: The invisible loss (story opening)
• Week 2: "Responding after 30 minutes costs you 21x in conversion. The first 5 minutes is everything."
  • Chapter: The quantified gap (data reveal)
• Week 3: "Instant auto-reply + mobile notifications = never miss the Golden Window."
  • Chapter: The solution (resolution)

Validation: Builds narrative arc ✓, Each advances story ✓

Strategy C: A/B/C Variants

Input: Monthly Theme = "Instagram Follower Leakage"

Output (Week 1):

• Variant A (Data-driven): "Instagram followers generate $79 per 1000. Owned contacts generate $582. That's 8x ROI."
• Variant B (Story-driven): "You built 10k Instagram followers. Then your account got suspended. All gone. Owned list survives platform risk."
• Variant C (Peer-driven): "Dubai clinics with 5k+ Instagram followers captured <2%. Those who built owned lists own 40% of their audience."

Validation: Same core message ✓, Different psychology ✓

Geographic Adaptation (Culture Map)

MENA Adaptation

Original (US-style): "Your sales data across 7 tools is costing you $47k in lost deals monthly. Here's the ROI breakdown."

MENA-adapted: "I noticed you're facing the same challenge Ahmed at [Company] mentioned—sales data scattered across tools. After working with him to unify everything, his team closed 40% more deals. Would love to share how."

Changes:

• Added relationship reference (Ahmed)
• Softened directness ("I noticed" vs "Your")
• Used "we" framing ("working with him")
• Implied outcome vs explicit claim

US Adaptation

Original (MENA-style): "Many founders we work with have found that unifying data sources creates meaningful improvements."

US-adapted: "Your sales data across 7 tools is costing you $47k monthly. Unified dashboard cuts that to zero."

Changes:

• Direct problem statement ("Your")
• Specific data ($47k)
• Clear outcome (cuts to zero)
• No softening or hedging

Germany Adaptation

Original (US-style): "Your sales data across 7 tools is costing you $47k monthly. Unified dashboard = predictable revenue."

Germany-adapted: "Systematic analysis of data fragmentation across disparate sales systems reveals a mean efficiency loss of 34% (n=147, p<0.01). Consolidation to a unified platform restores operational efficiency."

Changes:

• Formal language ("systematic analysis")
• Specific data (34%, n=147, p<0.01)
• Principle-first (efficiency loss → consolidation)
• Structured reasoning

Examples

Example 1: MENA SaaS - Intent Signal

Input:

• Signal Type: Intent
• Signal Subtype: Fragmentation Pain
• Signal Text: "Our sales data lives in 7 different tools. Decision paralysis is real."
• Monthly Theme: "Proof Silence - Data Fragmentation Crisis"
• Weekly Strategy: Different angles
• ICP: MENA SaaS Founders

Processing:

Week 1 Wedge (Identify problem):

Wedge: "Your sales data across 7 tools is creating decision paralysis. Unified dashboard = predictable revenue."

Validation:
- One-sentence test: ✓ PASS (1 sentence, no hedging)
- Specificity: ✓ PASS (7 tools, unified dashboard, predictable revenue)
- ICP resonance: ✓ PASS (MENA founders face this exact pain)
- Derived from monthly theme: ✓ PASS (data fragmentation)

Week 2 Wedge (Amplify cost):

Wedge: "Scattered data = invisible pipeline. Unified dashboard = predictable revenue."

Validation:
- One-sentence test: ✓ PASS
- Specificity: ✓ PASS (invisible pipeline = visibility loss)
- ICP resonance: ✓ PASS
- Derived from monthly theme: ✓ PASS

Week 3 Wedge (Provide proof):

Wedge: "5 MENA SaaS founders unified their scattered stack. They closed 40% more deals."

Validation:
- One-sentence test: ✓ PASS
- Specificity: ✓ PASS (5 founders, 40% more deals)
- ICP resonance: ✓ PASS (MENA peer proof)
- Derived from monthly theme: ✓ PASS (unified stack = data consolidation)

Output: 3 validated weekly wedges ready for asset-factory.

Example 2: US Real Estate - Multiple Signals

Input:

• Prospect 1 Signal: Intent: Speed Issues - "Losing leads to faster brokers"
• Prospect 2 Signal: Intent: Speed Issues - "Form fills at 2pm, reply at 5pm"
• Prospect 3 Signal: Intent: Solution Research - "Need automation for follow-up"
• Monthly Theme: "Response Silence - Golden Window Lost"
• Weekly Strategy: Sequential story
• ICP: US Real Estate Brokers

Processing (select highest priority Intent signal):

• All 3 are Intent signals
• 2 are Speed Issues (higher priority for Response Silence)
• Select Prospect 2 signal (most specific)

Week 1 Wedge (Story opening):

Wedge: "Your lead fills a form at 2pm. You reply at 5pm. They booked with someone else at 2:07pm."

Validation:
- One-sentence test: ✓ PASS
- Specificity: ✓ PASS (specific times: 2pm, 5pm, 2:07pm)
- ICP resonance: ✓ PASS (US brokers live this pain)
- Derived from signal: ✓ PASS (directly from Prospect 2)

Week 2 Wedge (Data reveal):

Wedge: "Responding after 30 minutes costs you 21x in conversion. The first 5 minutes is everything."

Validation:
- One-sentence test: ✓ PASS
- Specificity: ✓ PASS (21x, 30 minutes, 5 minutes)
- ICP resonance: ✓ PASS
- Sequential story: ✓ PASS (builds on Week 1)

Week 3 Wedge (Resolution):

Wedge: "Instant auto-reply + mobile notifications = never miss the Golden Window."

Validation:
- One-sentence test: ✓ PASS
- Specificity: ✓ PASS (instant, mobile, Golden Window)
- ICP resonance: ✓ PASS
- Sequential story: ✓ PASS (completes arc)

Output: 3 validated weekly wedges in narrative sequence.

Error Handling

Error 1: Wedge Fails One-Sentence Test

Symptom: Generated wedge requires multiple sentences Fix: Narrow signal focus, remove complexity Example: "Your sales data is scattered. This causes problems. We solve it." → "Your sales data across 7 tools is creating decision paralysis. Unified dashboard = predictable revenue."

Error 2: No Intent Signals Available

Symptom: Only Trust signals in validated prospect list Fix: Use Trust signals, note lower priority in output Example: "Week 1 uses Trust signal (Community Engagement) due to no Intent signals available."

Error 3: Wedge Too Generic

Symptom: Wedge lacks ICP-specific language Fix: Add ICP context (geography, vertical, specific pain) Example: "Better sales results" → "MENA SaaS founders closed 40% more deals after unifying scattered data"

Error 4: Weekly Wedges Not Related

Symptom: 3 wedges address different problems Fix: Realign all 3 to monthly theme Example: Week 1="Data scattered", Week 2="Slow response", Week 3="No proof" → All should focus on data fragmentation

Integration with Other Sub-Skills

Downstream Dependencies

After wedge-generator outputs 3 validated wedges:

asset-factory uses:

• 3 weekly wedges (exact text)
• ICP context
• Geographic market
• Channel mix
• To produce 42 assets (18 emails, 12 LinkedIn, 9 WhatsApp, 3 social)

Upstream Dependencies

Inputs from:

1. signal-detector: Validated signals (Fit PASS, Fresh, Trust/Intent classified)
2. campaign-strategist: Monthly theme, weekly strategy, ICP context
3. wedge-sentence-map.md: ICP-specific templates

Conclusion

The wedge-generator sub-skill ensures:

1. Signal-specific wedges (not generic value props)
2. One-sentence clarity (Hard Stop Rule 3)
3. Intent prioritization (Hard Stop Rule 4)
4. ICP resonance (templates + language)
5. Weekly consistency (all 3 relate to monthly theme)

Output: 3 validated, one-sentence wedges ready to power 42 multi-channel assets.

Next: Pass 3 wedges to asset-factory for email, LinkedIn, WhatsApp, and social production.