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GraphDone: Complete Technical Overview

This document contains the comprehensive technical documentation, architecture details, and implementation guides for GraphDone.

How GraphDone Works: A Visual Deep Dive

The Core Concept: Work as a Graph

Traditional project management tools organize work in linear lists or hierarchical trees. GraphDone models work as it actually exists - a network of interconnected outcomes, dependencies, and relationships.

graph TD
    subgraph "Traditional PM"
        A1[Manager] --> B1[Task 1]
        A1 --> B2[Task 2]
        A1 --> B3[Task 3]
        B1 --> C1[Subtask]
        B2 --> C2[Subtask]
    end
    
    subgraph "GraphDone"
        O1[User Auth] 
        O2[API Design]
        O3[Database]
        O4[Frontend]
        M1[Launch MVP]
        
        O3 -.-> O1
        O2 -.-> O3
        O1 -.-> O4
        O2 -.-> O4
        O1 --> M1
        O2 --> M1
        O3 --> M1
        O4 --> M1
    end
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Multi-Level Graph Navigation

Work is organized as interconnected graphs at different levels of detail. Users can navigate from high-level strategic goals down through projects and features to individual tasks, with the system dynamically showing appropriate detail levels.

graph TD
    subgraph "Strategic Level"
        S1[Company Goals]
        S2[Product Vision]
        S3[Market Expansion]
    end
    
    subgraph "Project Level"
        P1[User Authentication]
        P2[Mobile App]
        P3[Analytics Dashboard]
        P4[API Platform]
    end
    
    subgraph "Feature Level"
        F1[Login System]
        F2[Registration Flow]
        F3[Touch Interface]
        F4[Offline Mode]
    end
    
    subgraph "Task Level"
        T1[OAuth Integration]
        T2[Password Reset]
        T3[Gesture Recognition]
        T4[Data Sync]
    end
    
    S1 --> P1
    S1 --> P4
    S2 --> P2
    S3 --> P3
    
    P1 --> F1
    P1 --> F2
    P2 --> F3
    P2 --> F4
    
    F1 --> T1
    F2 --> T2
    F3 --> T3
    F4 --> T4
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Democratic Prioritization Process

Ideas can migrate inward through community validation, creating a natural innovation pipeline without requiring executive approval.

sequenceDiagram
    participant U as User
    participant I as Idea/Node
    participant C as Community
    participant S as System
    participant R as Resources
    
    U->>I: Create new idea
    Note over I: Starts at periphery<br/>Priority = 0.1
    
    I->>C: Visible to community
    C->>I: Anonymous rating & boosting
    
    alt Community validates idea
        C->>S: Positive feedback
        S->>I: Increase community priority
        Note over I: Migrates inward<br/>Priority = 0.4
        
        alt Continued validation
            C->>S: More positive feedback
            S->>I: Further priority increase
            Note over I: Moves to inner sphere<br/>Priority = 0.8
            S->>R: Allocate significant resources
        end
    else Community rejects idea
        C->>S: Negative/no feedback
        Note over I: Remains at periphery<br/>Gets minimal resources
    end
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Human-AI Collaboration Model

GraphDone treats AI agents as first-class citizens in the collaboration graph, not as separate tools or automations.

graph LR
    subgraph "Collaboration Graph"
        H1[👤 Human<br/>Designer]
        H2[👤 Human<br/>Developer] 
        A1[🤖 AI Agent<br/>Code Review]
        A2[🤖 AI Agent<br/>Testing]
        
        N1[Design System]
        N2[Component Library]
        N3[User Testing]
        N4[Performance Optimization]
        
        H1 --> N1
        H1 --> N2
        H2 --> N2
        A1 --> N2
        H2 --> N4
        A2 --> N4
        N2 --> N3
        A2 --> N3
        
        N1 -.-> N2
        N2 -.-> N4
    end
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Multi-Dimensional Priority System

Each node has three priority dimensions that combine into a computed priority determining its visibility and resource allocation across the graph hierarchy.

graph TB
    subgraph "Priority Calculation"
        E[Executive Priority<br/>0.0 - 1.0<br/>Weight: 40%]
        I[Individual Priority<br/>0.0 - 1.0<br/>Weight: 30%]
        C[Community Priority<br/>0.0 - 1.0<br/>Weight: 30%]
        
        E --> CALC[Priority Calculator]
        I --> CALC
        C --> CALC
        
        CALC --> CP[Computed Priority<br/>0.0 - 1.0]
        CP --> VIS[Graph Visibility<br/>& Resource Allocation]
    end
    
    subgraph "Resource Allocation"
        VIS --> RA{Priority Level}
        RA -->|0.8 - 1.0| FR[High Visibility<br/>Full resources<br/>Featured in overview]
        RA -->|0.5 - 0.8| SR[Standard Visibility<br/>Regular resources<br/>Shown in project view]
        RA -->|0.2 - 0.5| LR[Lower Visibility<br/>Background resources<br/>Detailed view only]
        RA -->|0.0 - 0.2| MR[Minimal Visibility<br/>Idle cycles<br/>Hidden by default]
    end
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Architecture Deep Dive

System Architecture Overview

GraphDone is built as a distributed, real-time system with clear separation between graph engine, API layer, and presentation layers.

graph TB
    subgraph "Presentation Layer"
        WEB[Web Application<br/>React + D3.js]
        MOBILE[Mobile App<br/>React Native]
        API_CLIENT[AI Agent SDK<br/>REST + GraphQL]
    end
    
    subgraph "API Layer"
        GQL[GraphQL Server<br/>Apollo Server]
        WS[WebSocket Server<br/>Real-time subscriptions]
        REST[REST Endpoints<br/>Agent integration]
    end
    
    subgraph "Business Logic"
        CORE[Graph Engine<br/>@graphdone/core]
        PRIORITY[Priority Calculator]
        ALGO[Graph Algorithms<br/>Path finding, cycles]
    end
    
    subgraph "Data Layer"
        DB[(PostgreSQL<br/>Graph relationships)]
        CACHE[(Redis<br/>Session & cache)]
        SEARCH[Search Index<br/>Node discovery]
    end
    
    WEB --> GQL
    MOBILE --> GQL
    API_CLIENT --> REST
    API_CLIENT --> GQL
    
    GQL --> CORE
    WS --> CORE
    REST --> CORE
    
    CORE --> PRIORITY
    CORE --> ALGO
    CORE --> DB
    
    GQL -.-> WS
    CORE -.-> CACHE
    DB -.-> SEARCH
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Data Flow Architecture

Real-time updates flow through the system ensuring all participants see changes immediately.

sequenceDiagram
    participant UI as Web/Mobile UI
    participant GQL as GraphQL Server
    participant CORE as Graph Engine
    participant DB as Database
    participant WS as WebSocket
    participant AGENT as AI Agent
    
    UI->>GQL: Create/Update Node
    GQL->>CORE: Process graph operation
    CORE->>CORE: Calculate new priorities
    CORE->>CORE: Update positions
    CORE->>DB: Persist changes
    
    CORE->>WS: Broadcast updates
    WS->>UI: Real-time position update
    WS->>AGENT: Notify of priority change
    
    AGENT->>GQL: Query updated graph state
    GQL->>CORE: Fetch current data
    CORE->>AGENT: Return graph snapshot
    
    Note over AGENT: AI processes changes<br/>and plans next actions
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Repository Structure

graphdone/
├── packages/
│   ├── core/              # Graph engine and algorithms
│   ├── server/            # GraphQL API server
│   ├── web/               # React web application
│   └── agent-sdk/         # SDK for AI agents (planned)
├── docs/
│   ├── api/               # API documentation
│   ├── guides/            # User and developer guides
│   ├── examples/          # Integration examples
│   └── deployment/        # Deployment guides
├── scripts/               # Development and deployment scripts
├── .github/workflows/     # CI/CD pipelines
└── deployment/           # Docker and deployment files

Technology Stack & Implementation

Technology Architecture

The system is built with modern, scalable technologies optimized for real-time collaboration and graph operations.

graph TB
    subgraph "Frontend Technologies"
        REACT[React 18 + TypeScript<br/>Component-based UI]
        D3[D3.js<br/>Graph visualization]
        APOLLO_CLIENT[Apollo Client<br/>GraphQL + caching]
        TAILWIND[Tailwind CSS<br/>Utility-first styling]
        VITE[Vite<br/>Fast development]
    end
    
    subgraph "Backend Technologies"
        NODE[Node.js + TypeScript<br/>Runtime environment]
        APOLLO_SERVER[Apollo Server<br/>GraphQL API]
        PRISMA[Prisma<br/>Database ORM]
        EXPRESS[Express<br/>HTTP server]
        GRAPHQL_WS[GraphQL-WS<br/>Real-time subscriptions]
    end
    
    subgraph "Data Technologies"
        POSTGRES[(PostgreSQL<br/>Primary database)]
        REDIS[(Redis<br/>Caching layer)]
        GRAPH_STRUCT[Custom Graph Engine<br/>In-memory operations]
    end
    
    subgraph "DevOps Technologies"
        DOCKER[Docker<br/>Containerization]
        GITHUB_ACTIONS[GitHub Actions<br/>CI/CD pipeline]
        TURBO[Turbo<br/>Monorepo builds]
        VITEST[Vitest<br/>Testing framework]
    end
    
    REACT --> APOLLO_CLIENT
    APOLLO_CLIENT --> APOLLO_SERVER
    APOLLO_SERVER --> PRISMA
    PRISMA --> POSTGRES
    
    NODE --> EXPRESS
    EXPRESS --> APOLLO_SERVER
    APOLLO_SERVER --> GRAPH_STRUCT
    GRAPH_STRUCT --> REDIS
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Core Graph Engine Implementation

The heart of GraphDone is a custom graph engine optimized for collaborative workflows and real-time updates.

classDiagram
    class Graph {
        -nodes: Map~NodeId, Node~
        -edges: Map~EdgeId, Edge~
        -adjacencyList: Map~NodeId, Set~NodeId~~
        +addNode(params) Node
        +removeNode(nodeId) boolean
        +addEdge(params) Edge
        +findPath(start, end) NodeId[]
        +detectCycles() NodeId[][]
        +getNodesByPriority(threshold) Node[]
    }
    
    class Node {
        +id: NodeId
        +type: NodeType
        +title: string
        +priority: Priority
        +position: GraphPosition
        +status: NodeStatus
        +contributors: ContributorId[]
        +dependencies: NodeId[]
        +updatePriority(updates)
        +addContributor(id)
        +addDependency(id)
    }
    
    class Priority {
        +executive: number
        +individual: number
        +community: number
        +computed: number
    }
    
    class PriorityCalculator {
        -executiveWeight: 0.4
        -individualWeight: 0.3
        -communityWeight: 0.3
        +calculate(priority) Priority
        +migratePriority(current, boost) Priority
        +calculateVisibilityFromPriority(priority) number
    }
    
    Graph --> Node
    Graph --> Edge
    Node --> Priority
    PriorityCalculator --> Priority
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Real-Time Update Flow

GraphDone maintains real-time synchronization across all clients using WebSocket subscriptions and optimistic updates.

sequenceDiagram
    participant UI1 as User Interface 1
    participant UI2 as User Interface 2
    participant GQL as GraphQL Server
    participant GRAPH as Graph Engine
    participant DB as Database
    participant WS as WebSocket Hub
    
    Note over UI1,WS: Initial connection setup
    UI1->>WS: Subscribe to graph updates
    UI2->>WS: Subscribe to graph updates
    
    Note over UI1,WS: User creates/updates node
    UI1->>GQL: Mutation: updateNodePriority
    Note over UI1: Optimistic update<br/>immediate UI feedback
    
    GQL->>GRAPH: Process priority update
    GRAPH->>GRAPH: Recalculate priorities
    GRAPH->>GRAPH: Update graph positions
    GRAPH->>DB: Persist changes
    
    GRAPH->>WS: Broadcast priorityChanged event
    WS->>UI1: Confirm update
    WS->>UI2: Real-time priority update
    
    Note over UI2: Node updates visibility<br/>and position in graph
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GraphQL Schema Architecture

The API is designed around graph operations and real-time collaboration patterns.

erDiagram
    Node ||--o{ NodeContributor : "has"
    Node ||--o{ Edge : "source"
    Node ||--o{ Edge : "target"
    Node ||--|| Priority : "has"
    Node ||--|| GraphPosition : "positioned_at"
    
    Contributor ||--o{ NodeContributor : "participates"
    
    Node {
        ID id PK
        NodeType type
        string title
        string description
        NodeStatus status
        JSON metadata
        DateTime createdAt
        DateTime updatedAt
    }
    
    Priority {
        float executive
        float individual
        float community
        float computed
    }
    
    GraphPosition {
        float x
        float y
        int level
        string parentId
    }
    
    Edge {
        ID id PK
        ID sourceId FK
        ID targetId FK
        EdgeType type
        float weight
        JSON metadata
    }
    
    Contributor {
        ID id PK
        ContributorType type
        string name
        string email
        JSON capabilities
    }
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Quick Start

One-Command Setup

GraphDone includes a comprehensive setup script that handles all prerequisites and configuration.

# Clone and setup
git clone https://github.com/GraphDone/GraphDone-Core.git
cd graphdone
./tools/setup.sh

The setup script will:

  1. ✅ Check prerequisites (Node.js 18+, Docker, npm)
  2. 📦 Install all dependencies with workspace configuration
  3. 🔧 Create environment files from examples
  4. 🐘 Start PostgreSQL and Redis databases
  5. 🗄️ Run database migrations and generate Prisma client
  6. 🏗️ Build all packages

Development Workflow

graph LR
    START[./tools/setup.sh] --> DEV[./tools/run.sh]
    DEV --> TEST[./tools/test.sh]
    TEST --> BUILD[./tools/build.sh]
    BUILD --> DEPLOY[./tools/deploy.sh]
    
    DEV -.-> CODE[Code Changes]
    CODE -.-> DEV
    
    subgraph "Available Commands"
        RUN1[./tools/run.sh --docker-dev]
        RUN2[./tools/test.sh --coverage]
        RUN3[./tools/test.sh --package core]
        BUILD1[./tools/build.sh --production]
    end
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Running the System

Start all development servers:

./tools/run.sh

This provides:

Testing Your Setup

Verify everything works with these quick tests:

# Test API health
curl http://localhost:4000/health

# Create a test node
curl -X POST http://localhost:4000/graphql \
  -H "Content-Type: application/json" \
  -d '{"query": "mutation { createNode(input: { type: TASK, title: \"My First Node\" }) { id title priority { computed } } }"}'

# Query all nodes
curl -X POST http://localhost:4000/graphql \
  -H "Content-Type: application/json" \
  -d '{"query": "{ nodes { id title type priority { computed } position { radius } } }"}'

Docker Development Options

For containerized development:

# Full Docker development environment
./tools/run.sh --docker-dev

# Production-like environment
./tools/run.sh --docker

# Individual service testing
docker-compose up -d postgres  # Database only

Development Tools Integration

graph TB
    subgraph "IDE Integration"
        VSCODE[VS Code<br/>TypeScript, ESLint]
        EXTENSIONS[Recommended Extensions<br/>Prisma, GraphQL, React]
    end
    
    subgraph "Testing Framework"
        VITEST[Vitest<br/>Unit & Integration]
        COVERAGE[Coverage Reports<br/>All packages]
        E2E[E2E Testing<br/>Playwright ready]
    end
    
    subgraph "Development Server"
        HMR[Hot Module Reload<br/>Instant updates]
        TYPESCRIPT[TypeScript<br/>Real-time checking]
        LINTING[ESLint + Prettier<br/>Code quality]
    end
    
    subgraph "Database Tools"
        PRISMA_STUDIO[Prisma Studio<br/>Database GUI]
        MIGRATIONS[Auto Migrations<br/>Schema changes]
        SEEDING[Data Seeding<br/>Test data]
    end
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Core Concepts

Graph Structure

  • Nodes: Outcomes, tasks, milestones, contributors (human and AI)
  • Edges: Dependencies, relationships, priorities
  • Hierarchy: Multi-level positioning with dynamic levels of detail

Priority System

  • Executive flags: Strategic priority signals from leadership
  • Individual priority: Personal background priority assignment
  • Democratic weighting: Anonymous community rating and boosting
  • Migration algorithms: Ideas gain visibility and resources based on validation

Agent Integration

  • Graph API: Agents read/write graph state through standard endpoints
  • Event system: Real-time notifications for graph changes
  • Resource allocation: Agents can request compute resources based on node priority
  • Collaborative protocols: Standard patterns for human-AI coordination

API Overview

GraphQL Schema

type Node {
  id: ID!
  type: NodeType!
  title: String!
  description: String
  position: GraphPosition!
  priority: Priority!
  contributors: [Contributor!]!
  dependencies: [Node!]!
  status: NodeStatus!
}

type Priority {
  executive: Float
  individual: Float
  community: Float
  computed: Float
}

Agent SDK Example

import { GraphDoneAgent } from '@graphdone/agent-sdk';

const agent = new GraphDoneAgent({
  apiKey: process.env.GRAPHDONE_API_KEY,
  graphUrl: 'https://api.graphdone.com'
});

// Listen for new high-priority outcomes
agent.subscribe('node.priorityChanged', async (node) => {
  if (node.priority.computed > 0.8) {
    await agent.requestResources({
      nodeId: node.id,
      resourceType: 'gpu',
      duration: '30m'
    });
  }
});

Implementation Status & Next Steps

✅ Completed Foundation

  • Core Graph Engine: Full implementation with priority calculation, pathfinding, cycle detection
  • GraphQL API: Complete server with real-time subscriptions
  • Database Layer: PostgreSQL with Prisma ORM and proper relationships
  • Web Application: React + D3.js visualization with responsive design
  • Development Infrastructure: Monorepo, testing, Docker, CI/CD
  • Documentation: Comprehensive guides with Mermaid diagrams

🚀 Ready for Development

# Get started in 30 seconds
git clone https://github.com/GraphDone/GraphDone-Core.git
cd graphdone
./tools/setup.sh
./tools/run.sh

Visit http://localhost:3000 to see the working application!

🛣️ Development Roadmap

Foundation (Completed) ✅

  • Core graph engine with priority calculation and algorithms
  • GraphQL API server with real-time subscriptions
  • React web application with D3.js visualization
  • Development infrastructure and CI/CD

Alpha Release

  • Mobile application for touch-first interaction
  • AI Agent SDK for first-class agent integration
  • Real-time collaboration polish and optimization

Beta Release

  • Advanced analytics and insights dashboard
  • Enterprise features and authentication
  • Performance scaling for large graphs

Production Release

  • Security hardening and audit compliance
  • Production deployment and monitoring
  • Third-party integrations and marketplace

Contributing

GraphDone is built for and by teams who think differently. We welcome contributions that advance our mission of democratic, graph-native coordination.

🎯 High-Impact Contribution Areas

  • Graph Algorithms: Enhance priority propagation and conflict resolution
  • Mobile Experience: Perfect touch interactions for 3D graph manipulation
  • AI Agent Integration: Build the SDK and example agents
  • Accessibility: Make graph visualization work for screen readers
  • Performance: Optimize for large graphs (1000+ nodes)
  • Neurodiversity Support: Design patterns for different cognitive styles

🔧 Development Workflow

# Set up development environment
./tools/setup.sh

# Make your changes
git checkout -b feature/your-improvement

# Test your changes
./tools/test.sh --coverage

# Build and verify
./tools/build.sh

# Submit your contribution
git push origin feature/your-improvement
# Open a Pull Request with clear description

Deployment

Self-Hosted

# Using Docker Compose
docker-compose -f docker-compose.prod.yml up -d

# Using Kubernetes
kubectl apply -f tools/deployment/k8s/

Cloud Hosting

  • AWS: ECS/EKS deployment guides in docs/deployment/aws/
  • GCP: GKE deployment guides in docs/deployment/gcp/
  • Azure: AKS deployment guides in docs/deployment/azure/

Roadmap

v0.1.0 - Alpha (Current)

  • Basic graph visualization
  • Mobile-responsive interface
  • Real-time collaboration
  • Agent SDK foundation
  • Democratic prioritization

v0.2.0 - Beta

  • Spherical coordinate system
  • Anonymous rating system
  • Advanced graph algorithms
  • Agent marketplace foundation
  • Enterprise authentication

v1.0.0 - Stable

  • Full agent ecosystem
  • Advanced analytics
  • Enterprise features
  • Third-party integrations
  • Performance optimization