Co-Sell Platform Edge Cases and Failure Modes

For Patent Application Support

Document Classification: Patent Sensitive - Edge Case Documentation Version: 1.0 Date: December 2025

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1. Partner Matching Edge Cases

1.1 Empty or Minimal Data Cases

Edge Case	Scenario	System Behavior
Missing ICP	Partner has not defined ICP	Use product categories and target markets as proxy; flag for completion
Empty Industries	Partner.icp.industries = []	Default to company industry; score as partial match only
No Target Markets	target_markets = []	Use geographic_regions as fallback; warn partner
Single Technology	technologies = ["AWS"]	Accept match if AWS is shared; lower weight for tech dimension

Handling:

IF partner.icp.industries.length == 0:
    partner.icp.industries = [partner.industry]
    data_quality_flag = "incomplete_icp"

IF partner.icp.technologies.length < 2:
    tech_weight = 0.10  // Reduce from 0.20
    redistribute_weight_to_other_dimensions()

1.2 Extreme Score Cases

Edge Case	Scenario	System Behavior
Perfect ICP Match	ICP score = 100	Accept but verify not same company; flag for manual review
Zero ICP Overlap	No shared dimensions	Disqualify with reason "No common target market"
High ICP, Zero Product	ICP=90, Product=0	Disqualify; competitors targeting same market
Low ICP, High Product	ICP=25, Product=95	Qualify but warn "Limited shared customer base"

Handling:

IF icp_score == 100:
    IF partner_a.company_id == partner_b.company_id:
        RETURN {error: "Cannot match with self"}
    ELSE:
        flag_for_review("Perfect ICP match - verify distinct companies")

IF icp_score > 0 AND icp_score < 20 AND product_score > 70:
    status = "qualified_with_warning"
    warning = "Strong product fit but limited ICP overlap - consider niche campaign"

1.3 Partner Tier Mismatches

Edge Case	Scenario	System Behavior
Premier + Select	Large tier gap	Qualify but flag power imbalance risk
Unknown Tier	Partner not in AWS program	Treat as "select" equivalent; flag for verification
Multiple Cloud	Partner is also Azure partner	Note in profile; no scoring impact

Handling:

tier_gap = ABS(TIER_INDEX[partner_a.tier] - TIER_INDEX[partner_b.tier])

IF tier_gap >= 2:
    risk_factors.add({
        type: "tier_imbalance",
        severity: "medium",
        description: "Significant partner tier difference may affect co-sell dynamics"
    })

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2. Brand Voice Merging Edge Cases

2.1 Tone Conflicts

Edge Case	Conflicting Tones	Resolution Strategy
Formal vs Casual	A: ["formal", "corporate"] B: ["casual", "playful"]	Default to midpoint "professional"; require manual approval
Technical vs Accessible	A: ["technical", "precise"] B: ["simple", "jargon-free"]	Use AI to suggest "technical accuracy with plain English explanations"
Aggressive vs Conservative	A: ["bold", "disruptive"] B: ["conservative", "measured"]	Flag for human decision; cannot auto-resolve

Handling:

FUNCTION resolve_tone_conflict(tone_a, tone_b):
    distance = ABS(spectrum[tone_a] - spectrum[tone_b])

    IF distance > 0.5:  // Major conflict
        IF can_find_middle_ground(tone_a, tone_b):
            RETURN {
                resolved_tone: middle_tone,
                confidence: "medium",
                requires_approval: true
            }
        ELSE:
            RETURN {
                error: "UNRESOLVABLE_TONE_CONFLICT",
                recommendation: "Require partner discussion",
                suggestion: "Consider audience-specific variants"
            }

2.2 Messaging Guideline Conflicts

Edge Case	Conflict Type	Resolution
Do vs Avoid Overlap	A.do includes what B.avoid	AI suggests compromise; flag for review
Contradictory Claims	A: "fastest" B: "most reliable"	Combine: "fast AND reliable" with supporting evidence
Competitor Mentions	A names B's competitor as comparison	Remove competitor references; focus on joint value

Handling:

FUNCTION identify_messaging_conflicts(brand_a, brand_b):
    conflicts = []

    // Check if A's "do" items are in B's "avoid"
    FOR item IN brand_a.messaging_guidelines.do:
        IF semantically_similar(item, brand_b.messaging_guidelines.avoid):
            conflicts.add({
                type: "do_avoid_conflict",
                a_wants: item,
                b_avoids: find_similar(item, brand_b.avoid),
                severity: calculate_conflict_severity(item)
            })

    RETURN conflicts

2.3 Empty or Minimal Brand Voice

Edge Case	Scenario	System Behavior
No Brand Voice	Partner hasn't configured	Use product description to infer; request completion
Missing Tone	tone = []	Default to ["professional"]; flag incomplete
No Pain Points	pain_points = []	Extract from product description via AI
Missing Keywords	keywords = []	Generate from product categories and description

Handling:

FUNCTION ensure_brand_voice_complete(partner):
    IF partner.brand_voice IS NULL:
        partner.brand_voice = infer_brand_voice(
            partner.product_description,
            partner.industry,
            partner.company_size
        )
        partner.brand_voice_status = "auto_generated"
        notify_partner("Please review auto-generated brand voice")

    IF partner.brand_voice.tone.length == 0:
        partner.brand_voice.tone = ["professional"]
        partner.brand_voice_status = "incomplete"

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3. Campaign Orchestration Edge Cases

3.1 Approval Workflow Edge Cases

Edge Case	Scenario	System Behavior
Approval Timeout	Partner doesn't respond in 7 days	Send reminder at day 3, escalate at day 5, pause campaign at day 7
Conflicting Edits	Both partners edit same content	Present diff; require reconciliation
Approval Revoked	Partner un-approves after approval	Halt publishing; notify both partners; restart approval
Partner Leaves	Company exits co-sell mid-campaign	Pause campaign; offer continuation options to remaining partner

Handling:

FUNCTION handle_approval_timeout(asset, days_pending):
    IF days_pending == 3:
        send_reminder(asset.pending_partner)

    IF days_pending == 5:
        escalate_to_partner_admin(asset.pending_partner)
        notify_other_partner("Waiting on partner approval")

    IF days_pending >= 7:
        asset.status = "stalled"
        campaign.status = "paused"
        notify_all_stakeholders("Campaign paused due to approval delay")
        offer_options([
            "Extend deadline",
            "Skip this asset",
            "Cancel campaign"
        ])

3.2 Content Generation Edge Cases

Edge Case	Scenario	System Behavior
AI Generation Fails	LLM returns error or timeout	Retry with exponential backoff (3 attempts); fall back to template
Content Too Short	Generated content < minimum length	Regenerate with explicit length requirement
Content Too Long	Exceeds platform limits (e.g., LinkedIn 3000 chars)	Auto-truncate with "[...]" and CTA link; notify for manual edit
Inappropriate Content	AI generates off-brand content	Flag for manual review; log for model improvement
Duplicate Content	Similar to previous campaign	Detect via embedding similarity; suggest variations

Handling:

FUNCTION generate_content_with_fallback(params):
    FOR attempt IN [1, 2, 3]:
        TRY:
            content = LLM_INVOKE(params)

            IF content.length < params.min_length:
                params.prompt += " Ensure response is at least {min_length} words."
                CONTINUE

            IF content.length > params.max_length:
                content = truncate_with_cta(content, params.max_length)

            IF is_duplicate(content, previous_campaigns):
                params.prompt += " Create unique content different from: {summary}"
                CONTINUE

            RETURN content

        CATCH error:
            WAIT(2 ^ attempt seconds)

    // All retries failed
    RETURN fallback_template(params)

3.3 Publishing Edge Cases

Edge Case	Scenario	System Behavior
Platform API Down	LinkedIn/email API unavailable	Queue for retry; notify partners of delay
Invalid Credentials	Partner OAuth token expired	Prompt re-authentication; hold publishing
Rate Limited	Too many API calls	Implement backoff; spread publishing over time
Content Rejected	Platform rejects content (policy)	Notify partners; flag for content revision
Timezone Mismatch	Partners in different timezones	Use partner's local timezone for "their" channel

Handling:

FUNCTION execute_publish(asset, channel):
    TRY:
        response = channel.api.publish(asset.content)

        IF response.status == "rate_limited":
            queue_for_retry(asset, delay = response.retry_after)
            RETURN {status: "queued", reason: "rate_limited"}

        IF response.status == "rejected":
            asset.status = "rejected_by_platform"
            notify_partners(
                "Content rejected by {channel}. Reason: {response.reason}"
            )
            RETURN {status: "failed", reason: response.reason}

        RETURN {status: "published", url: response.url}

    CATCH NetworkError:
        queue_for_retry(asset, delay = 300)  // 5 minutes
        notify_partners("Publishing delayed due to platform issues")

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4. Success Prediction Edge Cases

4.1 Data Availability Edge Cases

Edge Case	Scenario	System Behavior
New Partner	Zero historical co-sells	Use heuristic only; set confidence = "low"
New to Platform	Partner just joined	Use industry benchmarks; flag prediction as preliminary
Incomplete Profile	Missing key features	Note missing data; reduce confidence proportionally
Outlier History	One partner has 50+ co-sells	Cap historical weight to prevent over-influence

Handling:

FUNCTION calculate_prediction_confidence(features):
    base_confidence = 0.5

    // Data completeness factor
    available = count_non_null(features)
    total = count_all_features(features)
    completeness = available / total
    base_confidence += 0.25 * completeness

    // Historical data factor
    total_history = features.a_prev_cosells + features.b_prev_cosells

    IF total_history == 0:
        historical_factor = 0
        prediction_disclaimer = "No historical data - prediction is heuristic-based"
    ELSE IF total_history > 20:
        historical_factor = 0.25  // Cap influence
    ELSE:
        historical_factor = 0.25 * (total_history / 20)

    base_confidence += historical_factor

    RETURN MIN(base_confidence, 0.95)

4.2 Model Edge Cases

Edge Case	Scenario	System Behavior
Model Unavailable	ML service down	Use heuristic fallback; note in output
Prediction = 0	All factors negative	Return minimum 0.05 (nothing is impossible)
Prediction = 1	All factors perfect	Cap at 0.95 (nothing is certain)
Feature Out of Range	ICP score > 100 (data error)	Clamp to valid range; log anomaly

Handling:

FUNCTION get_prediction_safe(features):
    // Sanitize inputs
    features.icp_overlap = CLAMP(features.icp_overlap, 0, 100)
    features.product_complementarity = CLAMP(features.product_complementarity, 0, 100)
    features.market_alignment = CLAMP(features.market_alignment, 0, 100)

    TRY:
        prediction = ML_MODEL.predict(features)
    CATCH ModelUnavailable:
        prediction = heuristic_predict(features)
        prediction.source = "heuristic_fallback"

    // Enforce bounds
    prediction.probability = CLAMP(prediction.probability, 0.05, 0.95)

    RETURN prediction

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5. System-Level Failure Modes

5.1 Database Failures

Failure Mode	Impact	Recovery Strategy
Primary DB Down	All operations fail	Failover to replica; read-only mode
Write Timeout	Campaign creation fails	Retry with idempotency key; queue if persistent
Data Corruption	Invalid relationship data	Detect via checksums; restore from backup
Connection Pool Exhausted	Requests timeout	Implement circuit breaker; scale pool

5.2 AI/LLM Failures

Failure Mode	Impact	Recovery Strategy
API Timeout	Content generation fails	Retry with backoff; use cached/template content
Rate Limiting	Throughput reduced	Queue requests; implement token bucket
Model Hallucination	Incorrect content generated	Validation layer; human review for high-stakes content
Context Length Exceeded	Large partner profiles fail	Summarize inputs; chunk processing

5.3 Integration Failures

Failure Mode	Impact	Recovery Strategy
OAuth Expiry	Can't publish to channels	Proactive refresh; notify partner
Webhook Delivery Fail	Partner not notified	Retry queue; email fallback
Third-party API Change	Integration breaks	Version pinning; graceful degradation

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6. Business Logic Edge Cases

6.1 Relationship Edge Cases

Edge Case	Scenario	System Behavior
Self-Match Request	Partner tries to match with self	Reject with clear error
Duplicate Relationship	Relationship already exists	Return existing relationship; don't create duplicate
Circular Reference	A→B→C→A campaign chain	Allow; track lineage for analytics
Acquisition	Partner A acquires Partner B	Merge profiles option; notify of relationship impact

6.2 Campaign Edge Cases

Edge Case	Scenario	System Behavior
Overlapping Campaigns	Same partners, multiple campaigns	Allow; warn of audience fatigue
Campaign During Holiday	Publishing scheduled on holiday	Warn; suggest date adjustment
Zero Duration	duration_weeks = 0	Reject; minimum 1 week required
Very Long Campaign	duration_weeks > 12	Allow but warn of planning complexity

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7. Security Edge Cases

7.1 Access Control Edge Cases

Edge Case	Scenario	System Behavior
Unauthorized Access	User tries to view other's campaign	Return 403; log attempt
Role Escalation	Viewer tries to approve content	Reject action; audit log
Deactivated User	Former employee accesses system	Deny access; alert admin
Cross-Partner Data Leak	Bug exposes Partner A data to B	Input validation; output sanitization

7.2 Data Validation Edge Cases

Edge Case	Scenario	System Behavior
XSS in Content	Malicious script in brand voice	Sanitize all inputs; escape outputs
SQL Injection	Malicious company_name	Parameterized queries only
Oversized Payload	10MB brand voice JSON	Reject; enforce size limits
Invalid Unicode	Malformed characters	Normalize input; reject invalid

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8. Recovery Procedures

8.1 Campaign Recovery

FUNCTION recover_stalled_campaign(campaign_id):
    campaign = load_campaign(campaign_id)

    // Identify stall point
    stall_point = find_first_incomplete_step(campaign)

    SWITCH stall_point.type:
        CASE "approval_pending":
            send_escalation(stall_point.pending_partner)
            offer_skip_option(stall_point.asset)

        CASE "generation_failed":
            retry_generation(stall_point.asset)

        CASE "publish_failed":
            retry_publish(stall_point.asset)

        CASE "partner_inactive":
            offer_campaign_continuation_options()

    log_recovery_action(campaign_id, stall_point, action_taken)

8.2 Data Recovery

FUNCTION recover_corrupted_relationship(relationship_id):
    // Attempt to reconstruct from audit log
    audit_events = get_audit_log(relationship_id)

    IF audit_events.length > 0:
        reconstructed = replay_events(audit_events)
        IF validate_relationship(reconstructed):
            restore_relationship(reconstructed)
            RETURN {status: "recovered", method: "audit_replay"}

    // Fall back to backup
    backup = get_latest_backup(relationship_id)
    IF backup:
        IF validate_relationship(backup):
            restore_relationship(backup)
            RETURN {status: "recovered", method: "backup_restore"}

    // Manual intervention required
    alert_admin("Cannot auto-recover relationship {relationship_id}")
    RETURN {status: "manual_intervention_required"}

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Document Version: 1.0 For Patent Application Support Confidential - Edge Case Documentation