QUAD Sample Environment: GlobalRetail Inc.
A Realistic Enterprise Environment for QUAD Use Cases
Part of QUAD™ (Quick Unified Agentic Development) Methodology © 2025 Suman Addanke / A2 Vibe Creators LLC
Table of Contents
Company Overview
┌──────────────────────────────────────────────────────────────────────┐
│ GLOBALRETAIL INC. │
│ "Retail for the Modern World" │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ Industry: Retail / E-Commerce │
│ Founded: 1998 (started as brick & mortar) │
│ Employees: 8,500 globally │
│ IT Staff: ~450 (across all locations) │
│ Revenue: $2.8B annually │
│ Locations: 320 physical stores + e-commerce │
│ │
│ Digital Transformation Status: "In Progress" (since 2019) │
│ Technical Debt Level: HIGH (legacy systems from 2005-2015) │
│ │
└──────────────────────────────────────────────────────────────────────┘Company History
Technology Landscape
The "Zoo" of Technologies
┌──────────────────────────────────────────────────────────────────────┐
│ GLOBALRETAIL TECH STACK │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────────┐│
│ │ MODERN (2020+) ││
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ││
│ │ │ React │ │ Node.js │ │ Postgres │ │ AWS │ ││
│ │ │ Next.js │ │ Express │ │ (RDS) │ │ Lambda │ ││
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ ││
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ││
│ │ │ Kotlin │ │ Swift │ │ Redis │ │ Elastic │ ││
│ │ │ Android │ │ iOS │ │ Cache │ │ Search │ ││
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ ││
│ └─────────────────────────────────────────────────────────────────┘│
│ │
│ ┌─────────────────────────────────────────────────────────────────┐│
│ │ LEGACY (2005-2015) ││
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ││
│ │ │ Java 8 │ │ Oracle │ │ Vertica │ │ COBOL │ ││
│ │ │ Spring │ │ 11g R2 │ │ DW │ │ Batch │ ││
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ ││
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ││
│ │ │ .NET │ │ SQL │ │ IBM MQ │ │ Windows │ ││
│ │ │ 4.5 │ │ Server │ │ Queues │ │ Server │ ││
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ ││
│ └─────────────────────────────────────────────────────────────────┘│
│ │
│ ┌─────────────────────────────────────────────────────────────────┐│
│ │ TOOLS & PLATFORMS ││
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ││
│ │ │ GitHub │ │Confluence│ │ Jira │ │ Slack │ ││
│ │ │ Enterpr. │ │ Server │ │ Server │ │ Business │ ││
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ ││
│ │ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ││
│ │ │ Jenkins │ │ MS 365 │ │ Splunk │ │PagerDuty │ ││
│ │ │ CI/CD │ │ Suite │ │ Logs │ │ Alerts │ ││
│ │ └──────────┘ └──────────┘ └──────────┘ └──────────┘ ││
│ └─────────────────────────────────────────────────────────────────┘│
│ │
└──────────────────────────────────────────────────────────────────────┘Team Structure
IT Organization
┌──────────────────────────────────────────────────────────────────────┐
│ IT ORGANIZATION (~450 people) │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ CTO (Maria Chen) │
│ │ │
│ ┌────────────────────┼────────────────────┐ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ VP Digital │ │ VP Core │ │ VP Infra │ │
│ │ (Modern) │ │ (Legacy) │ │ (Platform) │ │
│ │ ~150 people │ │ ~180 people │ │ ~120 people │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ │ │ │ │
│ ┌──────┴──────┐ ┌──────┴──────┐ ┌──────┴──────┐ │
│ │ │ │ │ │ │ │
│ ▼ ▼ ▼ ▼ ▼ ▼ │
│ Web App Mobile E-Commerce Batch Cloud On-Prem │
│ Team Team Team Team Team Team │
│ (React) (iOS/ (Java/ (COBOL (AWS) (Data │
│ Android) Oracle) /SQL) Center) │
│ │
└──────────────────────────────────────────────────────────────────────┘Key Stakeholders
Pain Points (Pre-QUAD)
The Real Problems
┌──────────────────────────────────────────────────────────────────────┐
│ GLOBALRETAIL PAIN POINTS │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ PROBLEM 1: REQUIREMENT CHAOS │
│ ════════════════════════════ │
│ • Business writes vague requirements in Word docs │
│ • Developers interpret differently │
│ • 3-4 rounds of "that's not what I meant" │
│ • Average story takes 2.5 weeks (should take 3 days) │
│ │
│ PROBLEM 2: LEGACY KNOWLEDGE SILOS │
│ ════════════════════════════════ │
│ • Only 2 people understand the COBOL batch jobs │
│ • Oracle stored procedures: 500+ with no documentation │
│ • "Ask Bob" is the documentation strategy │
│ • Bob is retiring in 6 months │
│ │
│ PROBLEM 3: INTEGRATION NIGHTMARES │
│ ═══════════════════════════════ │
│ • Modern React app → Legacy Java → Oracle → Vertica │
│ • 47 different integration patterns │
│ • One change breaks 3 other systems │
│ • No one knows the full data flow │
│ │
│ PROBLEM 4: DEPLOYMENT FEAR │
│ ══════════════════════════ │
│ • "Deploy on Thursday" → "Pray on Friday" │
│ • Last 5 releases had rollbacks │
│ • No automated testing for legacy │
│ • Manual deployments take 4 hours │
│ │
│ PROBLEM 5: DATA QUALITY │
│ ════════════════════════ │
│ • Customer data in 7 different systems │
│ • No single source of truth │
│ • Analytics reports don't match │
│ • GDPR compliance is a nightmare │
│ │
└──────────────────────────────────────────────────────────────────────┘By the Numbers
Systems Inventory
Complete System Catalog
#### 1. E-Commerce Platform (Legacy Core)system_id: ECOM-001
name: "RetailCore E-Commerce"
status: CRITICAL
age: 17 years
owner: Priya Sharma (Dir. E-Commerce)
technology:
language: Java 8
framework: Spring 4.3 (EOL!)
database: Oracle 11g R2
app_server: WebLogic 12c
caching: Coherence
infrastructure:
location: On-premise data center
servers: 12 physical + 8 VM
load_balancer: F5 BIG-IP
storage: NetApp SAN
integrations:
inbound:
- POS systems (320 stores)
- Mobile app
- Partner APIs
outbound:
- Payment gateway (Stripe)
- Shipping (FedEx, UPS)
- Inventory (SAP)
- Data warehouse (Vertica)
pain_points:
- "Spring 4.3 is end-of-life, security patches not available"
- "Oracle 11g no longer supported by vendor"
- "No unit tests, 0% code coverage"
- "Only 3 developers understand the codebase"
- "Deployment takes 4 hours, requires 8 people"
revenue_at_risk: "$800M annually"
downtime_cost: "$50K per hour"
system_id: DW-001
name: "Analytics Data Warehouse"
status: CRITICAL
age: 13 years
owner: Mike Johnson (Dir. Analytics)
technology:
database: Vertica 9.2 (2 versions behind)
etl: Informatica PowerCenter 10.1
reporting: Tableau Server
scheduler: Control-M
infrastructure:
location: On-premise
cluster: 8-node Vertica cluster
storage: 45 TB (growing 2TB/month)
data_sources:
- E-Commerce (ECOM-001)
- POS transactions
- Customer master
- Inventory
- Marketing campaigns
pain_points:
- "Query performance degraded 40% over 2 years"
- "ETL jobs take 8 hours (used to be 2 hours)"
- "Cannot handle real-time analytics"
- "Vertica license costs $500K/year"
- "No one remembers why 200+ ETL jobs exist"
business_impact:
- "Daily sales report arrives at 11 AM (too late)"
- "Cannot do ML/AI on this platform"
- "Executives frustrated with stale data"
system_id: BATCH-001
name: "Overnight Batch System"
status: CRITICAL
age: 20 years
owner: Susan Miller (VP Core)
technology:
language: COBOL 85
scheduler: CA Workload Automation
database: DB2 on z/OS
file_transfer: Connect:Direct
batch_jobs:
total: 847 jobs
critical: 127 jobs
documented: 43 jobs (5%!)
average_runtime: 6 hours
key_processes:
- GL01: General ledger posting
- INV01: Inventory reconciliation
- PAY01: Payroll processing
- RPT01: Regulatory reporting
- CUS01: Customer data sync
pain_points:
- "Only Bob and Mary understand the code"
- "Bob retires in 6 months"
- "Mary is looking for new job"
- "No documentation for 95% of jobs"
- "One job failure causes 8-hour cascade"
- "Cannot find COBOL developers"
risk_level: EXTREME
system_id: MOB-001
name: "GlobalRetail Mobile Apps"
status: NEEDS_MODERNIZATION
age: 3 years (rewrite from 2015 version)
owner: Mobile Team (under VP Digital)
technology:
ios:
language: Swift 5
min_version: iOS 14
architecture: MVVM
ci_cd: Fastlane + GitHub Actions
android:
language: Kotlin
min_version: Android 8 (API 26)
architecture: MVVM + Hilt
ci_cd: Gradle + GitHub Actions
integrations:
- E-Commerce API (Java/Oracle)
- Push notifications (Firebase)
- Analytics (Mixpanel)
- Payments (Apple Pay, Google Pay, Stripe)
pain_points:
- "Depends on legacy Java API - often slow"
- "10% of features blocked by backend limitations"
- "No staging environment matches prod"
- "App store reviews: 3.2 stars (complaints about bugs)"
system_id: WEB-001
name: "RetailWeb (New)"
status: ACTIVE_DEVELOPMENT
age: 2 years
owner: Web App Team (under VP Digital)
technology:
frontend: React 18, Next.js 14
backend: Node.js 20, Express
database: PostgreSQL 15 (AWS RDS)
cache: Redis (ElastiCache)
search: Elasticsearch
hosting: AWS (ECS Fargate)
integrations:
- Legacy E-Commerce API (read-only)
- New microservices (Node.js)
- Mobile apps (shared API)
- Analytics (Segment → various)
pain_points:
- "Cannot write to legacy Oracle directly"
- "Data sync delays (15-min lag)"
- "Feature parity with legacy still at 70%"
- "Two codebases to maintain"
system_id: TOOLS-001
name: "Corporate Tool Stack"
status: ACTIVE
owner: IT Operations
tools:
source_control:
name: GitHub Enterprise
users: 400+
repos: 350+
documentation:
name: Confluence Server
version: 7.19
spaces: 85
pages: 12,000+
project_management:
name: Jira Server
version: 9.4
projects: 45
issues: 150,000+
communication:
name: Slack Business+
channels: 500+
users: 8,500
email:
name: Microsoft 365
users: 8,500
ci_cd:
name: Jenkins
version: 2.387
jobs: 200+
pipelines: 45
monitoring:
name: Splunk Enterprise
daily_ingestion: 500 GB
alerting:
name: PagerDuty
services: 75
on_call_schedules: 12
cloud:
primary: AWS (us-east-1)
services:
- EC2, ECS, Lambda
- RDS, ElastiCache, S3
- CloudFront, Route 53
- CloudWatch, X-Ray
monthly_spend: ~$180K
Use Case Scenarios
Ready-to-Use QUAD Scenarios
These scenarios can be used to demonstrate QUAD methodology:
Scenario 1: Modernize the COBOL Batch System
┌──────────────────────────────────────────────────────────────────────┐
│ SCENARIO: "Bob is Retiring" - COBOL Knowledge Transfer │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ SITUATION: │
│ • Bob (senior COBOL developer) retires in 6 months │
│ • 847 batch jobs, only 43 documented │
│ • No one else understands the code │
│ • Business cannot survive without these jobs │
│ │
│ QUAD APPROACH: │
│ │
│ Phase 1: Document (Story Agent) │
│ ├── Scan all 847 COBOL programs │
│ ├── Generate documentation using AI │
│ ├── Create dependency maps │
│ └── Identify critical paths │
│ │
│ Phase 2: Prioritize (Estimation Agent) │
│ ├── Rank jobs by business criticality │
│ ├── Estimate modernization effort per job │
│ └── Create modernization roadmap │
│ │
│ Phase 3: Modernize (Dev Agents) │
│ ├── Convert critical jobs to Java/Python │
│ ├── Run in parallel with COBOL │
│ └── Gradually retire COBOL │
│ │
│ LABELS: │
│ priority/P0, type/TECH_DEBT, circle/2-DEV, platform/BATCH │
│ complexity/ICOSAHEDRON (20 pts - Epic level) │
│ │
└──────────────────────────────────────────────────────────────────────┘Scenario 2: E-Commerce Platform Upgrade
┌──────────────────────────────────────────────────────────────────────┐
│ SCENARIO: "Spring 4.3 EOL" - Security Vulnerability │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ SITUATION: │
│ • Spring 4.3 reached end-of-life │
│ • Security team found 12 CVEs (3 critical) │
│ • Must upgrade to Spring Boot 3.2 │
│ • $800M revenue runs on this system │
│ │
│ QUAD APPROACH: │
│ │
│ Phase 1: Analysis (Code Agent + Security Agent) │
│ ├── Scan entire Java codebase (500K lines) │
│ ├── Identify all Spring dependencies │
│ ├── Map breaking changes from 4.3 → 6.0 → Boot 3.2 │
│ └── Generate upgrade stories automatically │
│ │
│ Phase 2: Test Strategy (QA Agent) │
│ ├── Generate regression test cases │
│ ├── Create API contract tests │
│ └── Performance benchmarks │
│ │
│ Phase 3: Incremental Upgrade (Dev Agents) │
│ ├── Module-by-module upgrade │
│ ├── Feature flag for rollback │
│ └── Zero-downtime deployment │
│ │
│ LABELS: │
│ priority/P0, type/SECURITY, type/TECH_DEBT, circle/2-DEV │
│ platform/API, complexity/DODECAHEDRON (12 pts) │
│ │
└──────────────────────────────────────────────────────────────────────┘Scenario 3: Vertica to Snowflake Migration
┌──────────────────────────────────────────────────────────────────────┐
│ SCENARIO: "Analytics Modernization" - Data Platform Migration │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ SITUATION: │
│ • Vertica license renewal: $500K/year │
│ • Performance degraded 40% │
│ • Cannot support ML/AI workloads │
│ • 200+ ETL jobs (many undocumented) │
│ • Migrate to Snowflake on AWS │
│ │
│ QUAD APPROACH: │
│ │
│ Phase 1: Discovery (Data Agent + Story Agent) │
│ ├── Catalog all Vertica tables (1,200+) │
│ ├── Map ETL job dependencies │
│ ├── Identify unused tables/jobs │
│ └── Generate migration stories │
│ │
│ Phase 2: Schema Conversion (DB Agent) │
│ ├── Convert Vertica DDL → Snowflake │
│ ├── Optimize for Snowflake architecture │
│ └── Data type mapping │
│ │
│ Phase 3: ETL Modernization (Dev Agent) │
│ ├── Informatica → dbt + Airflow │
│ ├── Incremental migration │
│ └── Parallel running for validation │
│ │
│ LABELS: │
│ priority/P1, type/INFRA, type/TECH_DEBT, circle/4-INFRA │
│ platform/BATCH, complexity/ICOSAHEDRON (20 pts) │
│ │
│ ROI: $500K/year license + $200K/year compute savings │
│ │
└──────────────────────────────────────────────────────────────────────┘Scenario 4: Mobile App Performance Fix
┌──────────────────────────────────────────────────────────────────────┐
│ SCENARIO: "3.2 Star Reviews" - Mobile App Crisis │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ SITUATION: │
│ • App Store rating dropped from 4.5 to 3.2 │
│ • Customer complaints: "App is slow", "Crashes on checkout" │
│ • Root cause: Legacy Java API response time 3-8 seconds │
│ • Mobile team blocked, cannot fix backend │
│ │
│ QUAD APPROACH: │
│ │
│ Phase 1: Root Cause Analysis (Code Agent + Perf Agent) │
│ ├── Profile Java API endpoints │
│ ├── Identify N+1 query issues │
│ ├── Map slow Oracle stored procedures │
│ └── Generate optimization stories │
│ │
│ Phase 2: Quick Wins (Dev Agent API) │
│ ├── Add Redis caching layer │
│ ├── Optimize top 10 slowest queries │
│ └── Implement pagination for large lists │
│ │
│ Phase 3: Mobile Fixes (Dev Agent iOS + Android) │
│ ├── Add offline mode │
│ ├── Implement optimistic UI │
│ └── Better error handling │
│ │
│ LABELS: │
│ priority/P0, type/BUG, circle/2-DEV │
│ platform/API, platform/IOS, platform/ANDROID │
│ complexity/OCTAHEDRON (8 pts) │
│ │
└──────────────────────────────────────────────────────────────────────┘Scenario 5: New Feature - Buy Online Pickup In-Store (BOPIS)
┌──────────────────────────────────────────────────────────────────────┐
│ SCENARIO: "BOPIS Feature" - Cross-System New Feature │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ SITUATION: │
│ • Business wants BOPIS (Buy Online, Pickup In Store) │
│ • Requires changes to: Web, Mobile, POS, Inventory, Notifications │
│ • Must integrate with 320 store systems │
│ • Launch in 3 months for holiday season │
│ │
│ QUAD APPROACH: │
│ │
│ Phase 1: Requirements (Story Agent) │
│ ├── Expand business requirement │
│ ├── Generate user stories for each platform │
│ ├── Identify integration points │
│ └── Flag risks and dependencies │
│ │
│ Phase 2: Estimation (Pipeline: Estimation) │
│ ├── Code Agent: API complexity │
│ ├── DB Agent: Schema changes │
│ ├── Flow Agent: Integration complexity │
│ └── Final estimate: DODECAHEDRON (12 pts) per platform │
│ │
│ Phase 3: Parallel Development (Pipeline: HYBRID) │
│ ├── Stage 1: [API, Database] parallel │
│ ├── Stage 2: [Web, iOS, Android] parallel │
│ ├── Stage 3: [POS Integration] sequential │
│ └── Stage 4: [QA] all platforms │
│ │
│ LABELS: │
│ priority/P1, type/FEATURE, circle/2-DEV │
│ platform/API, platform/WEB, platform/IOS, platform/ANDROID │
│ sprint/SPRINT-07, sprint/SPRINT-08, sprint/SPRINT-09 │
│ complexity/DODECAHEDRON (12 pts) │
│ │
│ GENERATED STORIES: 47 stories across 5 platforms │
│ │
└──────────────────────────────────────────────────────────────────────┘Scenario 6: Security Audit Remediation
┌──────────────────────────────────────────────────────────────────────┐
│ SCENARIO: "Security Audit Findings" - Compliance Urgent │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ SITUATION: │
│ • External security audit found 47 vulnerabilities │
│ • 8 Critical, 15 High, 24 Medium │
│ • PCI compliance at risk (handles credit cards) │
│ • Board requires remediation plan in 2 weeks │
│ │
│ QUAD APPROACH: │
│ │
│ Phase 1: Triage (Security Scanner Agent) │
│ ├── Scan all 47 findings │
│ ├── Auto-categorize by system │
│ ├── Estimate fix complexity │
│ └── Generate remediation stories │
│ │
│ Phase 2: Prioritized Backlog │
│ ├── Critical (8): P0, Sprint-Current │
│ ├── High (15): P1, Sprint-Current + Sprint-Next │
│ ├── Medium (24): P2, Backlog (plan within 90 days) │
│ └── Each story has specific fix instructions │
│ │
│ Phase 3: Fix & Verify (Security Pipeline) │
│ ├── Dev Agent: Implement fixes │
│ ├── Security Agent: Verify remediation │
│ ├── QA Agent: Regression testing │
│ └── Compliance Agent: Generate audit evidence │
│ │
│ LABELS: │
│ priority/P0-P2, type/SECURITY, circle/2-DEV + circle/3-QA │
│ platform/* (varies by finding) │
│ complexity/TETRAHEDRON to OCTAHEDRON (varies) │
│ │
│ BOARD REPORT: Auto-generated from story status │
│ │
└──────────────────────────────────────────────────────────────────────┘Quick Reference
System Codes
Key Contacts
Integration Map
┌─────────────────────────────────────────────────────────────────────┐
│ SYSTEM INTEGRATION MAP │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ [POS-320 stores] │
│ │ │
│ ▼ │
│ [BATCH-001 COBOL] ──────────────► [DW-001 Vertica] │
│ │ │ │
│ ▼ ▼ │
│ [ECOM-001 Java/Oracle] ◄──────── [Tableau Reports] │
│ │ │
│ ┌────┴────┐ │
│ ▼ ▼ │
│ [MOB-001] [WEB-001] │
│ iOS/And React │
│ │
└─────────────────────────────────────────────────────────────────────┘How to Use This Environment
This environment can be used for:
Part of QUAD™ (Quick Unified Agentic Development) Methodology © 2025 Suman Addanke / A2 Vibe Creators LLC