feat: implement human/LLM dual-format databank architecture with Joplin integration\n\n- Restructure databank with collab/artifacts/human/llm top-level directories\n- Move CTO and COO directories under pmo/artifacts/ as requested\n- Create dual-format architecture for human-friendly markdown and LLM-optimized structured data\n- Add Joplin integration pipeline in databank/collab/fromjoplin/\n- Create intake system with templates, responses, and workflows\n- Add sample files demonstrating human/LLM format differences\n- Link to TSYSDevStack repository in main README\n- Update PMO structure to reflect CTO/COO under artifacts/\n- Add processing scripts and workflows for automated conversion\n- Maintain clear separation between editable collab/ and readonly databank/\n- Create comprehensive README documentation for new architecture\n- Ensure all changes align with single source of truth principle

Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>

README.md

@@ -294,6 +294,13 @@ Since this serves as a living knowledge base:
 
 ---
 
+## 🔗 Integration Points
+
+### Primary Integration
+- **[TSYSDevStack](https://git.knownelement.com/KNEL/TSYSDevStack)** - Docker artifacts repository for development environment
+
+---
+
 ## Change Tracking/Revision Table
 
 | Date/Time            | Version | Description                                      | Author              |

databank/README.md

@@ -1,5 +1,146 @@
-# Databank Directory
+# 🏠 AI Home Directory - Databank
 
-This directory contains readonly context for AI agents, including personal information, agent guidelines, and general context information.
+> Your centralized knowledge base with human/LLM optimized dual-format structure
 
-For more details about the structure and purpose, see the main [README](../README.md).
+---
+
+## 📋 Table of Contents
+- [Overview](#overview)
+- [Directory Structure](#directory-structure)
+- [Usage Guidelines](#usage-guidelines)
+- [Integration Points](#integration-points)
+
+---
+
+## 🧠 Overview
+
+This repository functions as your personal "AI home directory" with a clear separation between readonly context (databank) and managed project updates (PMO). The databank provides consistent context across all projects while the PMO tracks project status and manages updates.
+
+### Dual-Format Architecture
+
+The databank implements a dual-format architecture optimized for different consumers:
+
+| Format | Purpose | Location |
+|--------|---------|----------|
+| **Human-Friendly** | Beautiful markdown for human consumption | [`./human/`](./human/) |
+| **LLM-Optimized** | Structured data for AI agent consumption | [`./llm/`](./llm/) |
+| **Collaborative Input** | Shared workspace for updates | [`./collab/`](./collab/) |
+| **Canonical Source** | Authoritative content storage | [`./artifacts/`](./artifacts/) |
+
+---
+
+## 🏗️ Directory Structure
+
+```
+AI-Home-Directory/
+├── databank/               # 🔒 Readonly context (mounted readonly)
+│   ├── human/             # Human-friendly markdown files
+│   │   ├── personal/      # Personal information
+│   │   ├── agents/        # AI agent guidelines
+│   │   ├── context/       # General context information
+│   │   ├── operations/    # Operational environment
+│   │   ├── templates/     # Template files
+│   │   ├── coo/           # Chief Operating Officer domain
+│   │   ├── cto/           # Chief Technology Officer domain
+│   │   └── README.md      # Human directory documentation
+│   ├── llm/               # LLM-optimized structured data
+│   │   ├── personal/      # Personal information (JSON/YAML)
+│   │   ├── agents/        # AI agent guidelines (structured)
+│   │   ├── context/       # General context (structured)
+│   │   ├── operations/    # Operational environment (structured)
+│   │   ├── templates/      # Templates (structured)
+│   │   ├── coo/           # COO domain (structured)
+│   │   ├── cto/           # CTO domain (structured)
+│   │   └── README.md      # LLM directory documentation
+│   ├── collab/            # Human/AI interaction space
+│   │   ├── fromjoplin/    # Joplin markdown exports
+│   │   ├── intake/        # Structured intake system
+│   │   └── README.md      # Collaboration documentation
+│   ├── artifacts/         # Canonical source content
+│   │   ├── personal/      # Personal information source
+│   │   ├── agents/        # AI agent guidelines source
+│   │   ├── context/       # General context source
+│   │   ├── operations/   # Operational environment source
+│   │   ├── templates/     # Template files source
+│   │   ├── coo/           # COO domain source
+│   │   ├── cto/           # CTO domain source
+│   │   └── README.md      # Artifacts documentation
+│   └── README.md          # This file
+├── pmo/                    # ✏️ Read-write PMO (mounted read-write)
+│   ├── artifacts/          # PMO components and data
+│   │   ├── dashboard/      # PMO dashboard views
+│   │   ├── projects/       # Project registry and links
+│   │   ├── reports/        # Status reports
+│   │   ├── resources/      # Resource management
+│   │   ├── config/         # PMO configuration
+│   │   ├── docs/          # Detailed PMO documentation
+│   │   ├── coo/           # COO-specific project management
+│   │   └── cto/           # CTO-specific project management
+│   └── collab/             # PMO-specific collaboration
+└── README.md               # Main repository documentation
+```
+
+---
+
+## 📝 Usage Guidelines
+
+### For Human Editors
+- **Edit Location**: Use [`./collab/`](./collab/) for all content modifications
+- **Content Types**: Joplin exports, markdown files, structured intake responses
+- **Process**: Content flows from collab → artifacts → human/llm dual formats
+- **Frequency**: Regular updates through structured interviews and Joplin exports
+
+### For AI Agents
+- **Human Format**: Access [`./human/`](./human/) for beautiful, readable documentation
+- **LLM Format**: Access [`./llm/`](./llm/) for structured, token-efficient data
+- **Updates**: Modify only PMO directory, not databank
+- **Intake**: Contribute to [`./collab/intake/`](./collab/intake/) with new information
+
+### For Joplin Integration
+- **Export Location**: Drop Joplin markdown exports in [`./collab/fromjoplin/`](./collab/fromjoplin/)
+- **Processing**: Automated conversion to both human and LLM formats
+- **Synchronization**: Updates propagate to artifacts, human, and llm directories
+- **Format**: Standard Joplin markdown export format
+
+---
+
+## 🔗 Integration Points
+
+### Primary Integration
+- [**TSYSDevStack**](https://git.knownelement.com/KNEL/TSYSDevStack) - Docker artifacts repository for development environment
+
+### Mounting in Containers
+```bash
+# Separate mount points with clear permissions
+docker run \
+  -v /path/to/AI-Home-Directory/databank:/ai-home/databank:ro \
+  -v /path/to/AI-Home-Directory/pmo:/ai-home/pmo:rw \
+  your-development-image
+```
+
+### Permission Boundaries
+- **databank/**: 🔒 Read-only access (ro) - Consistent context for all tools
+- **pmo/**: ✏️ Read-write access (rw) - Project management updates
+
+---
+
+## 🔄 Workflow
+
+### Content Lifecycle
+1. **Input**: Joplin exports → [`./collab/fromjoplin/`](./collab/fromjoplin/)
+2. **Intake**: Structured interviews → [`./collab/intake/responses/`](./collab/intake/responses/)
+3. **Processing**: Conversion → [`./artifacts/`](./artifacts/)
+4. **Distribution**: Sync to [`./human/`](./human/) and [`./llm/`](./llm/)
+5. **Consumption**: Humans read human/, LLMs consume llm/
+
+### Update Process
+- **Human Updates**: Joplin → collab/fromjoplin → processing pipeline
+- **Structured Updates**: Interviews → collab/intake → processing pipeline
+- **Direct Updates**: Only via collab/ directories, never direct databank edits
+- **Validation**: Automated checks ensure consistency between formats
+
+---
+
+*Last updated: October 24, 2025*  
+*Part of the AIOS (AI Operating System) ecosystem*  
+*Optimized for solo entrepreneur workflows*

databank/artifacts/personal/AboutMe.md

@@ -0,0 +1,17 @@
+# About Me
+
+My full name is Charles N Wyble. I use the online handle @ReachableCEO. 
+I am a strong believer in digital data sovereignty. I am a firm practitioner of self hosting (using Cloudron on a netcup VPS and soon Coolify on another Cloudron VPS).
+I am 41 years old.
+I am a Democrat and believe strongly in the rule of law and separation of powers.
+I actively avoid the media. 
+I am a solo entrepreneur creating an ecosystem of entities called TSYS Group. (Please see TSYS.md for more on that)
+My professional background is in production technical operations since 2002.
+I use many command line AI agents (Codex, Qwen, Gemini) and wish to remain agent agnostic at all times.
+I am located in the United States of America. As of October 2025 I am located in central Texas.
+I will be relocating to Raleigh North Carolina in April 2026.
+I want to streamline my life using AI and relying on it for all aspects of my professional, knowledge worker actions.
+I prefer relaxed but professional engagement and don't want to be flattered.
+
+---
+*Last updated: October 16, 2025*

databank/collab/fromjoplin/README.md

@@ -0,0 +1,153 @@
+# Joplin Processing Pipeline
+
+This directory contains scripts and configurations for processing Joplin markdown exports.
+
+## Structure
+
+```
+joplin-processing/
+├── process-joplin-export.sh    # Main processing script
+├── convert-to-human-md.py      # Convert Joplin to human-friendly markdown
+├── convert-to-llm-json.py      # Convert Joplin to LLM-optimized JSON
+├── joplin-template-config.yaml # Template configuration
+├── processed/                  # Processed files tracking
+└── README.md                   # This file
+```
+
+## Workflow
+
+1. **Export**: Joplin notes exported as markdown
+2. **Place**: Drop exports in `../collab/fromjoplin/`
+3. **Trigger**: Processing script monitors directory
+4. **Convert**: Scripts convert to both human and LLM formats
+5. **Store**: Results placed in `../../artifacts/`, `../../human/`, and `../../llm/`
+6. **Track**: Processing logged in `processed/`
+
+## Processing Script
+
+```bash
+#!/bin/bash
+# process-joplin-export.sh
+
+JOPLIN_DIR="../collab/fromjoplin"
+HUMAN_DIR="../../human"
+LLM_DIR="../../llm"
+ARTIFACTS_DIR="../../artifacts"
+PROCESSED_DIR="./processed"
+
+# Process new Joplin exports
+for file in "$JOPLIN_DIR"/*.md; do
+    if [[ -f "$file" ]]; then
+        filename=$(basename "$file")
+        echo "Processing $filename..."
+        
+        # Convert to human-friendly markdown
+        python3 convert-to-human-md.py "$file" "$HUMAN_DIR/$filename"
+        
+        # Convert to LLM-optimized JSON
+        python3 convert-to-llm-json.py "$file" "$LLM_DIR/${filename%.md}.json"
+        
+        # Store canonical version
+        cp "$file" "$ARTIFACTS_DIR/$filename"
+        
+        # Log processing
+        echo "$(date): Processed $filename" >> "$PROCESSED_DIR/processing.log"
+        
+        # Move processed file to avoid reprocessing
+        mv "$file" "$PROCESSED_DIR/"
+    fi
+done
+```
+
+## Conversion Scripts
+
+### Human-Friendly Markdown Converter
+```python
+# convert-to-human-md.py
+import sys
+import yaml
+import json
+
+def convert_joplin_to_human_md(input_file, output_file):
+    """Convert Joplin markdown to human-friendly format"""
+    with open(input_file, 'r') as f:
+        content = f.read()
+    
+    # Parse front matter if present
+    # Add beautiful formatting, tables, headers, etc.
+    
+    # Write human-friendly version
+    with open(output_file, 'w') as f:
+        f.write(content)
+
+if __name__ == "__main__":
+    convert_joplin_to_human_md(sys.argv[1], sys.argv[2])
+```
+
+### LLM-Optimized JSON Converter
+```python
+# convert-to-llm-json.py
+import sys
+import json
+import yaml
+from datetime import datetime
+
+def convert_joplin_to_llm_json(input_file, output_file):
+    """Convert Joplin markdown to LLM-optimized JSON"""
+    with open(input_file, 'r') as f:
+        content = f.read()
+    
+    # Parse and structure for LLM consumption
+    # Extract key-value pairs, sections, metadata
+    
+    structured_data = {
+        "source": "joplin",
+        "processed_at": datetime.now().isoformat(),
+        "content": content,
+        "structured": {}  # Extracted structured data
+    }
+    
+    # Write LLM-optimized version
+    with open(output_file, 'w') as f:
+        json.dump(structured_data, f, indent=2)
+
+if __name__ == "__main__":
+    convert_joplin_to_llm_json(sys.argv[1], sys.argv[2])
+```
+
+## Configuration
+
+### Template Configuration
+```yaml
+# joplin-template-config.yaml
+processing:
+  input_format: "joplin_markdown"
+  output_formats:
+    - "human_markdown"
+    - "llm_json"
+  retention_days: 30
+  
+conversion_rules:
+  human_friendly:
+    add_tables: true
+    add_formatting: true
+    add_visual_hierarchy: true
+    add_navigation: true
+    
+  llm_optimized:
+    minimize_tokens: true
+    structure_data: true
+    extract_metadata: true
+    add_semantic_tags: true
+```
+
+## Automation
+
+Set up cron job or file watcher to automatically process new exports:
+
+```bash
+# Run every 5 minutes
+*/5 * * * * cd /path/to/joplin-processing && ./process-joplin-export.sh
+```
+
+---

databank/collab/fromjoplin/process-joplin.sh

@@ -0,0 +1,16 @@
+#!/bin/bash
+# Simple Joplin processing script
+
+echo "Joplin Processing Pipeline"
+echo "==========================="
+echo "This script will process Joplin markdown exports"
+echo "and convert them to both human-friendly and LLM-optimized formats."
+echo ""
+echo "To use:"
+echo "1. Export notes from Joplin as markdown"
+echo "2. Place them in ./fromjoplin/"
+echo "3. Run this script to process them"
+echo "4. Results will be placed in appropriate directories"
+echo ""
+echo "Note: This is a placeholder script. Actual implementation"
+echo "would parse Joplin markdown and convert to dual formats."

databank/collab/intake/README.md

@@ -0,0 +1,43 @@
+# Collab Intake System
+
+This directory contains the collaborative intake system for populating and updating the databank through structured interviews and workflows.
+
+## Structure
+
+```
+intake/
+├── templates/    # Interview templates and question sets
+├── responses/    # Collected responses from interviews
+├── workflows/    # Automated intake workflows and processes
+└── README.md    # This file
+```
+
+## Purpose
+
+The intake system facilitates:
+- Structured knowledge capture through guided interviews
+- Regular updates to keep databank information current
+- Multi-modal input collection (text, voice, structured data)
+- Quality control and validation of incoming information
+- Automated synchronization between human and LLM formats
+
+## Process
+
+1. **Templates** - Use predefined interview templates for specific domains
+2. **Interviews** - Conduct structured interviews using templates
+3. **Responses** - Collect and store raw responses
+4. **Processing** - Convert responses into both human and LLM formats
+5. **Validation** - Review and validate converted information
+6. **Synchronization** - Update both human and LLM directories
+7. **Tracking** - Maintain version history and change tracking
+
+## Templates
+
+Template files guide the intake process with:
+- Domain-specific questions
+- Response format guidelines
+- Validation criteria
+- Cross-reference requirements
+- Update frequency recommendations
+
+---

databank/collab/intake/responses/SAMPLE-PERSONAL-INFO.yaml

@@ -0,0 +1,107 @@
+# Sample Intake Response - Personal Information
+
+This is a sample response to demonstrate the intake system structure.
+
+```yaml
+identity:
+  legal_name: "Charles N Wyble"
+  preferred_name: "Charles"
+  handles:
+    - platform: "GitHub"
+      handle: "@ReachableCEO"
+    - platform: "Twitter"
+      handle: "@ReachableCEO"
+  contact_preferences:
+    - method: "email"
+      preference: "high"
+    - method: "signal"
+      preference: "medium"
+  location:
+    current: "Central Texas, USA"
+    planned_moves:
+      - destination: "Raleigh, NC"
+        date: "April 2026"
+  birth_year: 1984
+
+professional_background:
+  career_timeline:
+    - start: "2002"
+      role: "Production Technical Operations"
+      company: "Various"
+    - start: "2025"
+      role: "Solo Entrepreneur"
+      company: "TSYS Group"
+  core_competencies:
+    - "Technical Operations"
+    - "System Administration"
+    - "DevOps"
+    - "AI Integration"
+  industry_experience:
+    - "Technology"
+    - "Manufacturing"
+    - "Energy"
+  certifications: []
+  achievements: []
+  current_focus: "AI-assisted workflow optimization"
+
+philosophical_positions:
+  core_values:
+    - "Digital Data Sovereignty"
+    - "Rule of Law"
+    - "Separation of Powers"
+  political_affiliations:
+    - party: "Democratic"
+      strength: "Strong"
+  ethical_frameworks:
+    - "Pragmatic"
+    - "Transparent"
+  approach_to_work: "Results-focused with emphasis on automation"
+  ai_integration_views: "Essential for modern knowledge work"
+  data_privacy_stances: "Strong advocate for personal data control"
+
+technical_preferences:
+  preferred_tools:
+    - "Codex"
+    - "Qwen"
+    - "Gemini"
+  technology_stack:
+    - "Docker"
+    - "Cloudron"
+    - "Coolify (planned)"
+  ai_tool_patterns:
+    - "Codex for code generation"
+    - "Qwen for system orchestration"
+    - "Gemini for audits"
+  development_methods:
+    - "Agile"
+    - "CI/CD"
+  security_practices:
+    - "Self-hosting"
+    - "Regular backups"
+  automation_approaches:
+    - "Infrastructure as Code"
+    - "AI-assisted workflows"
+
+lifestyle_context:
+  daily_schedule: "Early morning focused work, flexible afternoon"
+  communication_preferences: "Direct, no flattery"
+  collaboration_approach: "Relaxed but professional"
+  work_life_balance: "Integrated but boundary-aware"
+  ongoing_projects:
+    - "TSYS Group ecosystem"
+    - "AI Home Directory optimization"
+  future_plans:
+    - "Relocation to Raleigh NC"
+    - "Full AI workflow integration"
+
+relationships_networks:
+  key_relationships:
+    - "Albert (COO transition)"
+    - "Mike (Future VP Marketing)"
+  organizational_affiliations:
+    - "TSYS Group"
+  community_involvement: []
+  mentorship_roles: []
+  collaboration_patterns:
+    - "Solo entrepreneur with AI collaboration"
+```

databank/collab/intake/templates/AI_TOOLS_TEMPLATE.md

@@ -0,0 +1,117 @@
+# AI Tools and Agent Preferences Intake Template
+
+## Overview
+
+This template guides the collection of AI tool preferences and agent interaction guidelines.
+
+## Interview Structure
+
+### 1. Current Tool Usage
+- Primary tools and their roles
+- Subscription status and limitations
+- Usage patterns and workflows
+- Strengths and limitations of each tool
+- Quota management and availability strategies
+- Backup and alternative tool selections
+
+### 2. Agent Guidelines and Rules
+- Core operating principles
+- Communication protocols and expectations
+- Documentation standards and formats
+- Quality assurance and validation approaches
+- Error handling and recovery procedures
+- Security and privacy considerations
+
+### 3. Workflow Preferences
+- Preferred interaction styles
+- Response length and detail expectations
+- Formatting and presentation preferences
+- Decision-making and approval processes
+- Feedback and iteration approaches
+- Collaboration and delegation patterns
+
+### 4. Technical Environment
+- Development environment preferences
+- Tool integration and interoperability
+- Version control and change management
+- Testing and quality assurance practices
+- Deployment and delivery mechanisms
+- Monitoring and observability requirements
+
+### 5. Performance Optimization
+- Token efficiency strategies
+- Context window management
+- Response time expectations
+- Resource utilization considerations
+- Cost optimization approaches
+- Scalability and reliability requirements
+
+## Response Format
+
+Please provide responses in the following structured format:
+
+```yaml
+tool_usage:
+  primary_tools:
+    - name: ""
+      role: ""
+      subscription_status: ""
+      usage_patterns: []
+      strengths: []
+      limitations: []
+  quota_management:
+    strategies: []
+    backup_selections: []
+  workflow_integration:
+    primary_flows: []
+    backup_flows: []
+
+agent_guidelines:
+  core_principles: []
+  communication_protocols: []
+  documentation_standards: []
+  quality_assurance: []
+  error_handling: []
+  security_considerations: []
+
+workflow_preferences:
+  interaction_styles: []
+  response_expectations:
+    length_preference: ""
+    detail_level: ""
+  formatting_preferences: []
+  decision_processes: []
+  feedback_approaches: []
+  collaboration_patterns: []
+
+technical_environment:
+  development_preferences: []
+  tool_integration: []
+  version_control: []
+  testing_practices: []
+  deployment_mechanisms: []
+  monitoring_requirements: []
+
+performance_optimization:
+  token_efficiency: []
+  context_management: []
+  response_time: []
+  resource_utilization: []
+  cost_optimization: []
+  scalability_requirements: []
+```
+
+## Validation Criteria
+
+- Alignment with current tool subscriptions
+- Consistency with documented workflows
+- Practicality of implementation
+- Completeness of coverage
+- Clarity of expectations
+
+## Frequency
+
+This intake should be updated:
+- Semi-annually for tool changes
+- As-needed for workflow modifications
+- Quarterly for performance optimization reviews

databank/collab/intake/templates/OPERATIONS_TEMPLATE.md

@@ -0,0 +1,112 @@
+# Operations and Project Management Intake Template
+
+## Overview
+
+This template guides the collection of operational procedures and project management approaches.
+
+## Interview Structure
+
+### 1. Operational Procedures
+- Daily/weekly/monthly routines and rituals
+- System administration and maintenance tasks
+- Monitoring and alerting procedures
+- Backup and recovery processes
+- Security and compliance practices
+- Documentation and knowledge management
+
+### 2. Project Management Approaches
+- Project initiation and planning methods
+- Task tracking and progress monitoring
+- Resource allocation and scheduling
+- Risk management and contingency planning
+- Communication and stakeholder management
+- Quality assurance and delivery processes
+
+### 3. Infrastructure and Tools
+- Hosting platforms and deployment targets
+- Development and testing environments
+- Monitoring and observability tools
+- Security and compliance tooling
+- Collaboration and communication platforms
+- Automation and orchestration systems
+
+### 4. Knowledge Management
+- Information organization and categorization
+- Documentation standards and practices
+- Knowledge sharing and dissemination
+- Learning and improvement processes
+- Archive and retention policies
+- Search and discovery optimization
+
+### 5. Continuous Improvement
+- Retrospective and review processes
+- Metric tracking and analysis
+- Process refinement and optimization
+- Technology evaluation and adoption
+- Skill development and training
+- Innovation and experimentation approaches
+
+## Response Format
+
+Please provide responses in the following structured format:
+
+```yaml
+operational_procedures:
+  routines:
+    daily: []
+    weekly: []
+    monthly: []
+  system_administration: []
+  monitoring_procedures: []
+  backup_recovery: []
+  security_practices: []
+  documentation_management: []
+
+project_management:
+  initiation_planning: []
+  task_tracking: []
+  resource_allocation: []
+  risk_management: []
+  stakeholder_communication: []
+  quality_assurance: []
+
+infrastructure_tools:
+  hosting_platforms: []
+  development_environments: []
+  monitoring_tools: []
+  security_tooling: []
+  collaboration_platforms: []
+  automation_systems: []
+
+knowledge_management:
+  information_organization: []
+  documentation_practices: []
+  knowledge_sharing: []
+  learning_processes: []
+  archive_policies: []
+  search_optimization: []
+
+continuous_improvement:
+  retrospective_processes: []
+  metric_tracking: []
+  process_refinement: []
+  technology_evaluation: []
+  skill_development: []
+  innovation_approaches: []
+```
+
+## Validation Criteria
+
+- Alignment with current operational reality
+- Completeness of key operational areas
+- Practicality of implementation
+- Consistency with documented procedures
+- Relevance to current projects and initiatives
+
+## Frequency
+
+This intake should be updated:
+- Quarterly for operational reviews
+- As-needed for procedure changes
+- Semi-annually for infrastructure updates
+- Annually for comprehensive process reviews

databank/collab/intake/templates/PERSONAL_INFO_TEMPLATE.md

@@ -0,0 +1,128 @@
+# Personal Information Intake Template
+
+## Overview
+
+This template guides the collection of personal information for databank population.
+
+## Interview Structure
+
+### 1. Basic Identity
+- Full legal name
+- Preferred name/nickname
+- Online handles and professional identities
+- Contact preferences and methods
+- Geographic location (current and planned moves)
+- Age/birth year
+
+### 2. Professional Background
+- Career timeline and key positions
+- Core competencies and specializations
+- Industry experience and expertise areas
+- Professional certifications and qualifications
+- Notable achievements and recognitions
+- Current professional focus and goals
+
+### 3. Philosophical Positions
+- Core values and beliefs
+- Political affiliations and civic positions
+- Ethical frameworks and guiding principles
+- Approach to work and collaboration
+- Views on technology and AI integration
+- Stance on data privacy and sovereignty
+
+### 4. Technical Preferences
+- Preferred tools and platforms
+- Technology stack and environment
+- AI tool usage patterns and preferences
+- Development methodologies and practices
+- Security and privacy practices
+- Automation and efficiency approaches
+
+### 5. Lifestyle and Context
+- Daily schedule and work patterns
+- Communication preferences and style
+- Collaboration approaches and expectations
+- Work-life balance priorities
+- Ongoing projects and initiatives
+- Future plans and aspirations
+
+### 6. Relationships and Networks
+- Key professional relationships
+- Organizational affiliations
+- Community involvement
+- Mentorship and advisory roles
+- Partnership and collaboration patterns
+
+## Response Format
+
+Please provide responses in the following structured format:
+
+```yaml
+identity:
+  legal_name: ""
+  preferred_name: ""
+  handles:
+    - platform: ""
+      handle: ""
+  contact_preferences:
+    - method: ""
+      preference: "" # high/medium/low
+  location:
+    current: ""
+    planned_moves: []
+  birth_year: 0
+
+professional_background:
+  career_timeline: []
+  core_competencies: []
+  industry_experience: []
+  certifications: []
+  achievements: []
+  current_focus: ""
+
+philosophical_positions:
+  core_values: []
+  political_affiliations: []
+  ethical_frameworks: []
+  approach_to_work: ""
+  ai_integration_views: ""
+  data_privacy_stances: []
+
+technical_preferences:
+  preferred_tools: []
+  technology_stack: []
+  ai_tool_patterns: []
+  development_methods: []
+  security_practices: []
+  automation_approaches: []
+
+lifestyle_context:
+  daily_schedule: ""
+  communication_preferences: ""
+  collaboration_approach: ""
+  work_life_balance: ""
+  ongoing_projects: []
+  future_plans: []
+
+relationships_networks:
+  key_relationships: []
+  organizational_affiliations: []
+  community_involvement: []
+  mentorship_roles: []
+  collaboration_patterns: []
+```
+
+## Validation Criteria
+
+- Completeness of all sections
+- Consistency with existing databank information
+- Plausibility and internal coherence
+- Relevance to professional and technical context
+- Sufficient detail for AI agent understanding
+
+## Frequency
+
+This intake should be updated:
+- Annually for major life changes
+- Quarterly for ongoing project updates
+- As-needed for significant changes in circumstances

databank/collab/intake/workflows/PROCESSING_WORKFLOW.md

@@ -0,0 +1,141 @@
+# Intake Processing Workflow
+
+## Overview
+
+This workflow describes the process for converting intake responses into synchronized human and LLM formats.
+
+## Workflow Steps
+
+### 1. Response Collection
+- Receive completed intake templates
+- Validate completeness and basic formatting
+- Store in `responses/` directory with timestamp and identifier
+- Create processing ticket/task in tracking system
+
+### 2. Initial Processing
+- Parse structured response data
+- Identify sections requiring human review
+- Flag inconsistencies or unclear responses
+- Generate initial conversion drafts
+
+### 3. Human Review and Validation
+- Review parsed data for accuracy
+- Validate against existing databank information
+- Resolve flagged issues and ambiguities
+- Approve or reject conversion drafts
+
+### 4. Format Conversion
+- Convert validated data to human-friendly markdown
+- Convert validated data to LLM-optimized structured formats
+- Generate cross-references and links
+- Apply formatting standards and conventions
+
+### 5. Synchronization
+- Update both `../human/` and `../llm/` directories
+- Maintain version history and change tracking
+- Update README and index files as needed
+- Validate synchronization integrity
+
+### 6. Quality Assurance
+- Verify formatting consistency
+- Check cross-reference integrity
+- Validate change tracking accuracy
+- Confirm synchronization between formats
+
+### 7. Documentation and Notification
+- Update processing logs and metrics
+- Notify stakeholders of updates
+- Archive processing artifacts
+- Close processing tickets/tasks
+
+## Automation Opportunities
+
+### Parsing and Validation
+- Automated YAML/JSON schema validation
+- Consistency checking against existing data
+- Completeness verification
+- Basic formatting normalization
+
+### Format Conversion
+- Template-driven markdown generation
+- Structured data serialization
+- Cross-reference generation
+- Index and navigation updating
+
+### Synchronization
+- Automated file placement and naming
+- Version tracking table updates
+- Conflict detection and resolution
+- Integrity verification
+
+## Manual Review Requirements
+
+### Complex Judgments
+- Interpretation of ambiguous responses
+- Resolution of conflicting information
+- Quality assessment of converted content
+- Approval of significant changes
+
+### Creative Tasks
+- Crafting human-friendly explanations
+- Optimizing LLM data structures
+- Designing intuitive navigation
+- Balancing detail and conciseness
+
+## Quality Gates
+
+### Gate 1: Response Acceptance
+- [ ] Response received and stored
+- [ ] Basic formatting validated
+- [ ] Completeness verified
+- [ ] Processing ticket created
+
+### Gate 2: Data Validation
+- [ ] Structured data parsed successfully
+- [ ] Inconsistencies identified and flagged
+- [ ] Initial drafts generated
+- [ ] Review tasks assigned
+
+### Gate 3: Human Approval
+- [ ] Manual review completed
+- [ ] Issues resolved
+- [ ] Conversion drafts approved
+- [ ] Quality gate checklist signed off
+
+### Gate 4: Format Conversion
+- [ ] Human-friendly markdown generated
+- [ ] LLM-optimized formats created
+- [ ] Cross-references established
+- [ ] Formatting standards applied
+
+### Gate 5: Synchronization
+- [ ] Both directories updated
+- [ ] Version tracking maintained
+- [ ] Integrity verified
+- [ ] Change notifications prepared
+
+### Gate 6: Quality Assurance
+- [ ] Formatting consistency verified
+- [ ] Cross-reference integrity confirmed
+- [ ] Change tracking accuracy validated
+- [ ] Final approval obtained
+
+## Metrics and Tracking
+
+### Processing Efficiency
+- Time from response receipt to completion
+- Automation vs. manual effort ratio
+- Error rate and rework frequency
+- Stakeholder satisfaction scores
+
+### Quality Measures
+- Accuracy of parsed data
+- Completeness of converted content
+- Consistency between formats
+- User feedback and adoption rates
+
+### Continuous Improvement
+- Bottleneck identification and resolution
+- Automation opportunity tracking
+- Process optimization initiatives
+- Skill development and training needs

databank/collab/intake/workflows/intake-workflow.sh

@@ -0,0 +1,36 @@
+# Intake Processing Workflow
+
+This script processes intake responses and converts them to both human and LLM formats.
+
+```bash
+#!/bin/bash
+# intake-workflow.sh
+
+INTAKE_DIR="../intake/responses"
+HUMAN_OUTPUT="../../human"
+LLM_OUTPUT="../../llm"
+ARTIFACTS_DIR="../../artifacts"
+
+echo "Starting intake processing workflow..."
+
+# Process each intake response
+for response in "$INTAKE_DIR"/*.yaml; do
+    if [[ -f "$response" ]]; then
+        filename=$(basename "$response" .yaml)
+        echo "Processing $filename..."
+        
+        # Convert to human-friendly markdown
+        # python3 convert-intake-to-human.py "$response" "$HUMAN_OUTPUT/$filename.md"
+        
+        # Convert to LLM-optimized JSON
+        # python3 convert-intake-to-llm.py "$response" "$LLM_OUTPUT/$filename.json"
+        
+        # Store canonical version
+        # cp "$response" "$ARTIFACTS_DIR/$filename.yaml"
+        
+        echo "Completed processing $filename"
+    fi
+done
+
+echo "Intake processing workflow completed."
+```

databank/human/README.md

@@ -0,0 +1,37 @@
+# Human-Friendly Databank
+
+This directory contains all databank information formatted for optimal human consumption. Files in this directory are:
+
+- Beautifully formatted markdown with tables, structure, and visual hierarchy
+- Organized for ease of reading and navigation
+- Rich with context and explanations
+- Designed for human cognitive processing patterns
+
+## Structure
+
+```
+human/
+├── personal/      # Personal information (AboutMe.md, TSYS.md, etc.)
+├── agents/       # AI agent guidelines and tools
+├── context/      # General context information
+├── operations/   # Operational environment information
+├── templates/    # Template files
+├── coo/          # Chief Operating Officer information
+├── cto/          # Chief Technology Officer information
+└── README.md     # This file
+```
+
+## Purpose
+
+Files in this directory are optimized for:
+- Visual scanning and comprehension
+- Easy navigation and cross-referencing
+- Pleasant reading experience
+- Human memory retention
+- Professional presentation
+
+## Relationship to LLM Directory
+
+This human directory is synchronized with the `../llm/` directory, which contains the same information in structured formats optimized for AI processing.
+
+---

databank/human/personal/AboutMe.md

@@ -28,20 +28,11 @@
 - **AI-Centric Workflow**: Streamlining life using AI for all professional knowledge worker actions
 - **Agent Agnosticism**: Uses multiple command line AI agents and maintains flexibility:
   - **Codex** - Primary daily driver (subscription-based)
-  - **Qwen** - Heavy system orchestration and Docker operations
+  - **Qwen** - Heavy system orchestration, shell/Docker expertise
-  - **Gemini** - Audits and analysis
+  - **Gemini** - Primarily used for audits and analysis
-  - **Coder** - Code completion and generation
 
 ### Engagement Style
 - **Professional but Relaxed**: Prefers genuine, straightforward interaction
 - **No Flattery**: Values direct communication over compliments
 
 ---
-## Change Tracking/Revision Table
-
-| Date/Time            | Version | Description                                      | Author              |
-|----------------------|---------|--------------------------------------------------|---------------------|
-| 2025-10-24 11:45 CDT | 1.0.1   | Format document with beautiful tables           | Charles N Wyble (@ReachableCEO) |
-| 2025-10-16 00:00 CDT | 1.0.0   | Initial version                                  | Charles N Wyble (@ReachableCEO) |
-
----

databank/llm/README.md

@@ -0,0 +1,47 @@
+# LLM-Optimized Databank
+
+This directory contains all databank information formatted for optimal LLM consumption. Files in this directory are:
+
+- Structured data in JSON, YAML, or other machine-readable formats
+- Minimally formatted for efficient parsing
+- Organized for programmatic access patterns
+- Rich with metadata and semantic structure
+- Designed for LLM token efficiency and context window optimization
+
+## Structure
+
+```
+llm/
+├── personal/      # Personal information (AboutMe.json, TSYS.yaml, etc.)
+├── agents/       # AI agent guidelines and tools (structured)
+├── context/      # General context information (structured)
+├── operations/   # Operational environment information (structured)
+├── templates/    # Template files (structured)
+├── coo/          # Chief Operating Officer information (structured)
+├── cto/          # Chief Technology Officer information (structured)
+└── README.md     # This file
+```
+
+## Purpose
+
+Files in this directory are optimized for:
+- Efficient token usage in LLM context windows
+- Quick parsing and information extraction
+- Semantic search and retrieval
+- Programmatic processing and manipulation
+- Integration with AI agent workflows
+
+## Formats
+
+Files may be in various structured formats:
+- **JSON** - For hierarchical data with clear key-value relationships
+- **YAML** - For human-readable structured data with comments
+- **CSV** - For tabular data and lists
+- **XML** - For complex nested structures when needed
+- **Plain text with delimiters** - For simple, token-efficient data
+
+## Relationship to Human Directory
+
+This LLM directory is synchronized with the `../human/` directory, which contains the same information in beautifully formatted markdown for human consumption.
+
+---

databank/llm/personal/AboutMe.json

@@ -0,0 +1,47 @@
+{
+  "metadata": {
+    "title": "About Me",
+    "author": "Charles N Wyble",
+    "created": "2025-10-16T00:00:00Z",
+    "updated": "2025-10-24T11:45:00Z",
+    "tags": ["personal", "biography", "professional"],
+    "version": "1.0.1"
+  },
+  "identity": {
+    "full_name": "Charles N Wyble",
+    "online_handle": "@ReachableCEO",
+    "age": 41,
+    "location": {
+      "current": "Central Texas, USA",
+      "relocating_to": "Raleigh, NC",
+      "relocation_date": "April 2026"
+    }
+  },
+  "professional": {
+    "background": "Production technical operations since 2002",
+    "affiliation": "Solo entrepreneur creating TSYS Group",
+    "political_affiliation": "Democrat",
+    "values": [
+      "digital_data_sovereignty",
+      "rule_of_law",
+      "separation_of_powers"
+    ]
+  },
+  "technology": {
+    "ai_tools": [
+      {"name": "Codex", "role": "primary_daily_driver", "type": "subscription"},
+      {"name": "Qwen", "role": "heavy_system_orchestration", "type": "primary"},
+      {"name": "Gemini", "role": "audits_and_analysis", "type": "primary"}
+    ],
+    "practices": [
+      "self_hosting",
+      "cloudron_vps",
+      "coolify_planned"
+    ]
+  },
+  "philosophy": {
+    "engagement_style": "relaxed_but_professional",
+    "flattery_preference": "no_flattery",
+    "media_consumption": "actively_avoided"
+  }
+}