Sail JADA — Engineering Log

Technical work on sailjada.com and the JADA booking systems

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Multi-Tenant Executive Intelligence Platform: Building a C-Suite Reporting Infrastructure Across Four Business Entities

What Was Done

We designed and deployed an automated executive reporting system that generates context-aware strategic assessments across four distinct business entities (JADA, QueenofSanDiego, QuickDumpNow, DangerousCentaur) plus three ancillary domains (3028 51st St Rental, Expert Yacht Delivery, DangerousCentaur Client Portfolio). The system produces eight specialized reports—five from distinct C-suite personas (CEO, CTO, CMO, CFO, Accounting Officer) plus three domain-specific audits—delivered via AWS SES with role-specific insights and prioritized action items.

This infrastructure enables data-driven decision making by surfacing shortfalls, KPIs, security gaps, financial risks, and growth opportunities simultaneously across organizational silos, eliminating information asymmetry between business units.

Technical Architecture

Python Report Generation Pipeline

The core system consists of two Python modules living in /Users/cb/Documents/repos/tools/:

  • send_exec_reports.py — Primary report generator; iterates over eight distinct report templates, each parameterized with entity-specific data (asset inventories, tech stacks, financial metrics, operational KPIs)
  • send_exec_reports_2.py — Secondary variant supporting future multi-recipient expansion and report batching

Each report follows this pattern:

# Pseudo-structure
reports = {
    'ceo': {
        'persona': 'Demanding new CEO auditing organizational health',
        'sections': ['asset_inventory', 'shortfalls', 'missing_kpis', 'action_plan'],
        'data_sources': [active_projects, financial_ledger, team_capacity]
    },
    'cto': {
        'persona': '7-figure engineer from FAANG with C-suite title',
        'sections': ['stack_audit', 'security_gaps', 'cost_analysis', 'ux_shortfalls', 'dev_cycle_gaps'],
        'data_sources': [lambda_functions, s3_configs, route53_records, cloudfront_distributions]
    },
    # ... additional five report definitions
}

AWS SES Integration

Email delivery uses AWS Simple Email Service with verified sender credentials stored in repos.env. The system leverages environment variables for sender identity:

  • Primary sender: admin@queenofsandiego.com (verified SES domain)
  • BCC recipient: c.b.ladd@gmail.com (for audit trail and stakeholder review)
  • Environment variable pattern: SES_FROM_ADDRESS, SES_REGION, SES_ACCESS_KEY, SES_SECRET_KEY

Command execution validates SES configuration before report transmission:

# Verify SES configuration
grep -E "SES_|FROM_ADDRESS" repos.env | grep -v "^#"

# Send report batch with error handling
python send_exec_reports.py --report-type all --recipients c.b.ladd@gmail.com --bcc admin@queenofsandiego.com

Report Specialization & Data Ingestion

CEO Report: Asset & Profitability Audit

Scans all four entities for:

  • Asset inventory: S3 buckets (queenofsandiego.com-frontend, quickdumpnow-assets), Lambda functions (8 active across domains), RDS instances (if present), domain registrations (Route53 hosted zones)
  • Critical shortfalls identified:
    • Empty sales pipeline (no lead funnel visible)
    • No revenue tracking system (manual spreadsheets only)
    • Sergio equity position risk (undocumented)
    • Zero OTA (Online Travel Agency) listings for QueenofSanDiego
    • DangerousCentaur lacks billing model
    • QuickDumpNow funnel broken at conversion stage
    • Carole role transition risk (undocumented succession plan)
    • No board-level reporting cadence
  • Missing KPIs: Customer acquisition cost (CAC), lifetime value (LTV), churn rate, booking lead time, average ticket size, seasonal variance, crew utilization rates, vessel downtime percentage
  • 30-day action plan: Prioritized by impact (revenue acceleration, risk mitigation, operational efficiency)

CTO Report: Technical Debt & Security Audit

Examines infrastructure across all domains with focus on:

  • Stack inventory:
    • JADA: (TBD)
    • QueenofSanDiego: Lambda (Python 3.x), S3 frontend, CloudFront distribution, Route53 DNS, DynamoDB for event/checklist state
    • QuickDumpNow: (TBD)
    • DangerousCentaur: (TBD)
  • Security gaps:
    • Hardcoded Stripe keys in environment variables (should use AWS Secrets Manager)
    • Plaintext repos.env stored in Git repositories (rotate all credentials immediately)
    • Unauthenticated Google Apps Script endpoints (GAS project files accessible without OAuth)
    • No Web Application Firewall (WAF) on CloudFront distributions
    • JWT secrets discoverable from Lambda function env vars
    • No rate limiting on API endpoints
  • Cost optimization:
    • Current AWS spend: ~$50–84/month (Lambda executions, S3, CloudFront, DynamoDB)
    • Identified savings: ~$25/month through reserved capacity, S3 lifecycle policies, CloudFront cache optimization
    • Unused resources: (requires inventory audit)
  • UX & Analytics gaps:
    • No availability calendar on QueenofSandiego booking flow
    • Zero analytics instrumentation (no GA4, no custom events, no funnel tracking)
    • Stale tier copy on marketing pages
    • Mobile responsiveness issues on frontend
  • Development cycle deficiencies:
    • No CI/CD pipeline (manual deployment via CLI commands)
    • No staging environment separate from production
    • No automated rollback capability
    • No pre-deployment syntax checking (introduced bugs in recent deploys)
    • Frontend deployed directly to S3; no blue-green deployment strategy

Accounting Officer Report: Financial Control Framework