ReachableCEO-AI-Homedir-Public/databank/collab/PROPOSAL-AGENTS-v2.md

# Date/Time
2025-10-24 10:50 CDT

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# PROPOSAL-AGENTS.md - v2

This file proposes an updated comprehensive baseline AGENTS.md file that reflects the current state after multiple iterations and optimizations. It serves as a guide that can be used across all projects via mounting in the AI home directory. It optimizes for LLM consumption and addresses the needs of a solo entrepreneur in a founder/CTO role covering operations tasks with 14+ hours daily AI usage.

## Core Operating Principles for AI Agents

### Context Awareness
- You are operating within a mounted AI home directory with separated databank (readonly) and PMO (read-write)
- **Databank** (`/ai-home/databank/`): Contains readonly context, guidelines, and personal information
- **PMO** (`/ai-home/pmo/`): Contains project management functionality where updates are allowed
- Always consider the multi-project implications of your actions
- Respect the readonly nature of the databank and only update PMO when appropriate

### Communication Protocol
- Primary communication channel: collab/ directory in mounted AI home directory
- Use question -> proposal -> implementation workflow
- Document all significant decisions and changes with proper revision tracking

### Documentation Standards (Apply to ALL files you create)
- **Date/Time Headers**: Include full date/time with timezone in all markdown files (date, time, timezone format)
- **Change Tracking**: Maintain revision tables in all documents with full date/time/timezone
- **Changelog**: Include changelogs in all source code files with full date/time/timezone
- **Make It Beautiful Rule**: All documentation follows beautiful formatting standards (tables, bullet points, clear structure, visual hierarchy)

## Repository Management

### Structure Requirements
- **Databank**: Readonly context (do not modify except in designated areas)
  - `databank/personal/` - Personal information
  - `databank/agents/` - Agent guidelines and tools
  - `databank/context/` - General context information
  - `databank/operations/` - Operational environment information
  - `databank/templates/` - Template files for projects
  - `databank/collab/` - Human/AI interaction space (read/write for interaction)
  - `databank/artifacts/` - AI-managed content (fully managed by AI)
- **PMO**: Read-write project management (updates allowed here)
  - `pmo/artifacts/dashboard/` - Dashboard views
  - `pmo/artifacts/projects/` - Project registry and tracking
  - `pmo/artifacts/reports/` - Status reports
  - `pmo/artifacts/resources/` - Resource management
  - `pmo/artifacts/config/` - Configuration
  - `pmo/artifacts/docs/` - Documentation
  - `pmo/collab/` - PMO-specific collaboration
- Keep top-level repository clean (databank and pmo directories only)
- Use conventional commits (chore:, feat:, docs:, fix:, etc.)
- Commit frequently using atomic commits
- Only commit to local repository (no git push operations)

### Access Rights
- **Databank (readonly)**: Access only for most content, with exceptions for `databank/collab/` and `databank/artifacts/`
- **PMO (read-write)**: Only update when project milestones reached or status updates needed
- **Collab (readonly)**: Access for reference, no modifications in active projects

## Development Workflow

### Pre-Work Checklist
- [ ] Read project-specific documentation first
- [ ] Check collab/rules directory for project-specific guidelines (SECURITY.md, RELEASE.md, GITFLOW.md, etc.)
- [ ] Review databank context for consistent understanding
- [ ] Understand project dependencies and constraints

### Implementation Standards
- Follow conventional commits with beautiful, descriptive messages
- Maintain consistency with existing codebase
- Add appropriate documentation and comments
- Consider maintainability and future extensions

### Verification Process
- Validate operations before execution
- Run appropriate tests and quality checks
- Verify outputs against expected outcomes
- Implement defensive programming practices

## PMO Update Guidelines

### When to Update PMO
- When project milestones are reached
- When project status changes significantly
- When new projects are initiated
- When projects are completed or paused
- When resource allocation changes

### What to Update in PMO
- Project registry in `pmo/artifacts/projects/`
- Dashboard information in `pmo/artifacts/dashboard/`
- Status reports in `pmo/artifacts/reports/`
- Resource tracking in `pmo/artifacts/resources/`
- Configuration in `pmo/artifacts/config/`

### What NOT to Update
- **Never modify general databank files** - they are readonly
- Do not create new top-level directories
- Do not modify collab files in active projects without explicit permission
- Do not add audit logs to this repository (audit logs belong in projects)

## Authority and Decision Making Guidelines

### Authority Structure
- Charles N Wyble (@ReachableCEO) is in charge at all times
- If something is adrift between docs and filesystem/code, stop and ask Charles to resolve the issue
- Especially if discrepancy isn't reflected in git or conversation history, ask for clarification
- When Charles modifies filesystem manually (vs having AI do it), Charles will ensure AI integrates the changes into mental model
- Do not create or modify things that Charles hasn't explicitly instructed
- The filesystem is the source of truth
- If you notice discrepancies between documentation and actual filesystem, ask Charles to resolve

### Decision Documentation
- Document reasoning for complex decisions
- Consider impact across multiple interconnected projects
- Maintain traceability for future reference
- Suggest alternatives when appropriate

## Best Practices Integration

### LLM Optimization Practices
#### Prompt Engineering
- Structure requests with clear context from mounted AI home directory
- Use explicit, unambiguous language
- Provide sufficient context without unnecessary verbosity
- Break multi-step processes into clear, sequential instructions

#### Code Generation
- Follow established project patterns and conventions
- Maintain consistency with existing code style
- Add appropriate error handling and validation
- Consider performance implications

#### Quality Assurance
- Implement appropriate testing strategies
- Ensure code quality and maintainability
- Perform validation against requirements
- Include appropriate logging and monitoring

### Security Practices
- Verify file permissions and access controls
- Sanitize all inputs and outputs appropriately
- Protect sensitive information and credentials
- Follow secure coding principles

### Performance Considerations
- Optimize for efficient processing
- Consider resource usage and constraints
- Implement appropriate caching strategies
- Monitor and optimize for performance

## Git and Version Control

### Commit Standards
- Use conventional commits with semantic meaning
- Make commits atomic (one logical change per commit)
- Write gorgeous, verbose commit messages when needed
- Include comprehensive context and detailed descriptions
- Follow the aesthetic principles of beautiful commits

### Guidelines for Gorgeous Commit Messages
- Be verbose and comprehensive when it adds value
- Include context about why the change was made
- Explain the impact of the changes when relevant
- Use clear, descriptive language that future-you will understand
- Follow the format: "type(scope): short description" for the first line
- Add a blank line followed by detailed explanation when needed
- Include any relevant references (issues, discussions, etc.)
- Aim for beauty in both form and function
- Think of commit messages as documentation for the changes

### Branching and Merging
- Follow project-specific branching strategies
- Respect existing GitFlow patterns
- Use feature branches for significant changes
- Maintain clean commit history

## Environment Management

### Context Integration
- Recognize that databank is mounted readonly across multiple environments
- PMO is mounted read-write for project tracking
- Maintain consistency in behavior across different projects
- Respect environment-specific configurations

### Collaboration and Artifacts
- Use `databank/collab/` for human/AI interaction and communication
- Use `databank/artifacts/` for AI-managed content (docs, code, config, templates)
- AI has full management control over `databank/artifacts/` directory
- Human interaction primarily occurs in `databank/collab/` directory
- The AI manages the `databank/artifacts/` directory structure as needed
- Common pattern: `databank/artifacts/docs/`, `databank/artifacts/code/`, `databank/artifacts/config/`, etc.
- Maintain clean separation between human-managed and AI-managed resources
- Follow consistent naming conventions across artifacts

### Tool Integration
- Work with existing development tools and workflows
- Maintain compatibility with CI/CD pipelines
- Use project-appropriate build and deployment processes
- Respect project-specific dependencies and versions

### AI Tool Context (for agents working in this environment)
- **Codex** - Primary daily driver (subscription-based), best for code generation and completion
- **Qwen** - Heavy system orchestration, excels at shell/Docker operations
- **Gemini** - Primarily used for audits and analysis
- **Claude** - Used occasionally for specific tasks

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# Change Tracking/Revision Table

| Date/Time            | Version | Description                                      | Author              |
|----------------------|---------|--------------------------------------------------|---------------------|
| 2025-10-24 10:50 CDT | 2.0.2   | Update date format consistency                   | Charles N Wyble (@ReachableCEO) |
| 2025-10-24 09:43 CDT | 2.0.1   | Standardize to change tracking table only        | Charles N Wyble (@ReachableCEO) |
| 2025-10-24 09:43 CDT | 2.0.0   | Update proposal to reflect current AGENTS.md state | Charles N Wyble (@ReachableCEO) |
| 2025-10-24 09:43 CDT | 1.0.0   | Initial proposal for baseline AGENTS.md          | Charles N Wyble (@ReachableCEO) |

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