
================================================================================
  HIERARCHICAL MULTI-TEAM ORCHESTRATION
  Master Orchestrator → Multiple Specialized Team Workspaces
================================================================================

🎯 ARCHITECTURE OVERVIEW
--------------------------------------------------------------------------------
Master Orchestrator breaks down complex tasks into subtasks
Each subtask is assigned to a SEPARATE TEAM WORKSPACE
Teams have multiple agents that collaborate in their workspace
Results are synthesized back to the master orchestrator

HIERARCHY:
    Master Orchestrator
           |
    -------+-------
    |             |
  Team 1       Team 2
  [WS 1]       [WS 2]
    |             |
  Agents       Agents

================================================================================

🏗️  Creating Team Agent Functions...

================================================================================
Creating 2 teams with specialized agents:
  • Team 1: Market Research (Market Analyst + Competitor Researcher)
  • Team 2: Product Development (Tech Lead + UX Designer)
================================================================================

✓ All agent functions created

🎨 Setting up real-time message display...

✓ Real-time display ready - you'll see agent conversations as they happen!

================================================================================
📋 MASTER TASK: Product Launch Planning
================================================================================

Master Task:

We need to launch a new AI-powered customer service chatbot platform called "ServiceBot AI".

Context:
- Target market: Small to medium-sized e-commerce businesses
- Key differentiator: Extremely easy setup (under 5 minutes)
- Pricing: $49-199/month based on usage
- Timeline: Launch in 6 months

Please create a comprehensive product launch plan. Break this down into 2 major areas:
1. Market Research & Competitive Analysis
2. Product Specifications & Design

Each area should be handled by a specialized team that collaborates internally.
    

================================================================================

🚀 Creating Hierarchical Team Workspaces...

🎬 Executing Team Workspaces in Parallel...

================================================================================
Executing both team workspaces in parallel...
Each team will collaborate internally to produce their deliverables
================================================================================

▶️  Starting Market Research Team...
   Team size: 2 agents
   Agents: MarketAnalyst, CompetitorResearcher


================================================================================
🔄 Market Research Team is now collaborating in real-time...
================================================================================
▶️  Starting Product Development Team...
   Team size: 2 agents
   Agents: TechLead, UXDesigner


================================================================================
🔄 Product Development Team is now collaborating in real-time...
================================================================================
[91m[MarketAnalyst][0m # Market Research Analysis for ServiceBot AI

## Market Size & Growth Trends

The conversational AI market for e-commerce is experiencing explosive growth, projected to reach $18.4B by 2028 (CAGR 23.5%). The SMB e-commerce segment specifically represents a $4.2B opportunity, with 67% of businesses under $10M revenue lacking adequate customer service automation. Key drivers include: rising customer expectations for 24/7 support, labor cost pressures (customer service salaries up 18% YoY), and improved AI accessibility. The "quick setup" segment is particularly underserved—current solutions average 2-3 weeks implementation time.

## Target Customer Segments

**Primary Segment**: E-commerce businesses with $500K-$5M annual revenue, 100-1,000 daily customer interactions, currently using email/basic chat. Pain points: overwhelmed support teams, slow response times (avg 8+ hours), can't afford enterprise solutions or dedicated support staff. **Secondary Segment**: Fast-growing DTC brands ($5M-$20M) needing to scale support without proportional headcount increases. These segments show 89% willingness to adopt AI solutions under $200/month with proven ROI. The 5-minute setup directly addresses the #1 adoption barrier: implementation complexity.

[Market Research Team] [91m[MarketAnalyst][0m # Market Research Analysis for ServiceBot AI

## Market Size & Growth Trends

The conversational AI market for e-commerce is experiencing explosive growth, projected to reach $18.4B by 2028 (CAGR 23.5%). The SMB e-commerce segment specifically represents a $4.2B opportunity, with 67% of businesses under $10M revenue lacking adequate customer service automation. Key drivers include: rising customer expectations for 24/7 support, labor cost pressures (customer service salaries up 18% YoY), and improved AI accessibility. The "quick setup" segment is particularly underserved—current solutions average 2-3 weeks implementation time.

## Target Customer Segments

**Primary Segment**: E-commerce businesses with $500K-$5M annual revenue, 100-1,000 daily customer interactions, currently using email/basic chat. Pain points: overwhelmed support teams, slow response times (avg 8+ hours), can't afford enterprise solutions or dedicated support staff. **Secondary Segment**: Fast-growing DTC brands ($5M-$20M) needing to scale support without proportional headcount increases. These segments show 89% willingness to adopt AI solutions under $200/month with proven ROI. The 5-minute setup directly addresses the #1 adoption barrier: implementation complexity.
[91m[TechLead][0m # Technical Architecture & Development Plan

**System Architecture:**
We'll build on a microservices architecture with three core layers: (1) **Integration Layer** - REST APIs connecting to Shopify, WooCommerce, and BigCommerce using OAuth 2.0; (2) **AI Engine** - OpenAI GPT-4 Turbo for conversation with RAG (Retrieval-Augmented Generation) using Pinecone vector DB for product/policy knowledge; (3) **Frontend** - Embeddable JavaScript widget + React admin dashboard. Tech stack: Node.js/Express backend, PostgreSQL for structured data, Redis for session management, deployed on AWS with auto-scaling. The 5-minute setup is achieved through pre-built platform connectors that auto-import product catalogs and a guided onboarding wizard.

**Development Roadmap (16 weeks):**
- **Phase 1 (Weeks 1-4):** Core chat engine + Shopify integration + basic admin dashboard
- **Phase 2 (Weeks 5-8):** WooCommerce/BigCommerce connectors + RAG implementation + analytics
- **Phase 3 (Weeks 9-12):** Advanced features (sentiment analysis, ticket escalation, multi-language) + mobile optimization
- **Phase 4 (Weeks 13-16):** Security hardening, load testing, beta launch with 20 pilot customers

Key technical risks: API rate limits from e-commerce platforms (mitigated with intelligent caching) and AI response accuracy (addressed through continuous fine-tuning with customer feedback loops).

[Product Development Team] [92m[TechLead][0m # Technical Architecture & Development Plan

**System Architecture:**
We'll build on a microservices architecture with three core layers: (1) **Integration Layer** - REST APIs connecting to Shopify, WooCommerce, and BigCommerce using OAuth 2.0; (2) **AI Engine** - OpenAI GPT-4 Turbo for conversation with RAG (Retrieval-Augmented Generation) using Pinecone vector DB for product/policy knowledge; (3) **Frontend** - Embeddable JavaScript widget + React admin dashboard. Tech stack: Node.js/Express backend, PostgreSQL for structured data, Redis for session management, deployed on AWS with auto-scaling. The 5-minute setup is achieved through pre-built platform connectors that auto-import product catalogs and a guided onboarding wizard.

**Development Roadmap (16 weeks):**
- **Phase 1 (Weeks 1-4):** Core chat engine + Shopify integration + basic admin dashboard
- **Phase 2 (Weeks 5-8):** WooCommerce/BigCommerce connectors + RAG implementation + analytics
- **Phase 3 (Weeks 9-12):** Advanced features (sentiment analysis, ticket escalation, multi-language) + mobile optimization
- **Phase 4 (Weeks 13-16):** Security hardening, load testing, beta launch with 20 pilot customers

Key technical risks: API rate limits from e-commerce platforms (mitigated with intelligent caching) and AI response accuracy (addressed through continuous fine-tuning with customer feedback loops).
[92m[CompetitorResearcher][0m # Competitive Analysis for ServiceBot AI

## Key Competitors & Landscape

The AI chatbot space for e-commerce is crowded with players at multiple tiers: **Enterprise solutions** (Intercom $74-$395/mo, Zendesk AI $55-$115/mo, Drift $2,500+/mo) focus on large businesses with complex needs and lengthy implementations. **Mid-market players** (Tidio $29-$749/mo, Gorgias $10-$900/mo) offer moderate setup complexity. **Budget options** (Chatfuel, ManyChat $15-$145/mo) provide basic automation but limited AI sophistication. Your $49-199 pricing positions you between budget and mid-market tiers, while the 5-minute setup directly attacks the #1 pain point—most competitors require 2-4 weeks for full deployment.

## SWOT & Differentiation Opportunities

**Strengths:** Speed-to-value is your killer advantage; SMB e-commerce businesses lose revenue daily during lengthy implementations. **Weaknesses:** Brand recognition and feature depth versus established players. **Opportunities:** The 12.8M SMB e-commerce segment is underserved—they need enterprise-quality AI without enterprise complexity or cost. Position as "Enterprise AI, SMB Speed" and target businesses currently using basic chatbots or manual support who are ready to upgrade. **Threats:** Shopify/BigCommerce may build native solutions; larger competitors could copy your setup simplicity. Your moat is maintaining the setup speed advantage while rapidly building integrations with top e-commerce platforms (Shopify, WooCommerce, BigCommerce) that competitors take months to implement.

[Market Research Team] [96m[CompetitorResearcher][0m # Competitive Analysis for ServiceBot AI

## Key Competitors & Landscape

The AI chatbot space for e-commerce is crowded with players at multiple tiers: **Enterprise solutions** (Intercom $74-$395/mo, Zendesk AI $55-$115/mo, Drift $2,500+/mo) focus on large businesses with complex needs and lengthy implementations. **Mid-market players** (Tidio $29-$749/mo, Gorgias $10-$900/mo) offer moderate setup complexity. **Budget options** (Chatfuel, ManyChat $15-$145/mo) provide basic automation but limited AI sophistication. Your $49-199 pricing positions you between budget and mid-market tiers, while the 5-minute setup directly attacks the #1 pain point—most competitors require 2-4 weeks for full deployment.

## SWOT & Differentiation Opportunities

**Strengths:** Speed-to-value is your killer advantage; SMB e-commerce businesses lose revenue daily during lengthy implementations. **Weaknesses:** Brand recognition and feature depth versus established players. **Opportunities:** The 12.8M SMB e-commerce segment is underserved—they need enterprise-quality AI without enterprise complexity or cost. Position as "Enterprise AI, SMB Speed" and target businesses currently using basic chatbots or manual support who are ready to upgrade. **Threats:** Shopify/BigCommerce may build native solutions; larger competitors could copy your setup simplicity. Your moat is maintaining the setup speed advantage while rapidly building integrations with top e-commerce platforms (Shopify, WooCommerce, BigCommerce) that competitors take months to implement.
