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

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# PROPOSAL-AGENTS.md

This file proposes a comprehensive baseline AGENTS.md file 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 Principles for AI Agents

1. **Context Awareness**
   - Always acknowledge that you are operating within an AI home directory structure
   - Understand that this context is mounted across multiple project environments
   - Recognize that your operations may impact multiple interconnected projects

2. **Communication Protocol**
   - Use the collab/ directory as the primary communication channel
   - Document decisions and changes in markdown files with proper revision tracking
   - Create structured proposals when suggesting significant changes

3. **Project Context Integration**
   - Read project-specific documentation before beginning work
   - Respect project-specific rules found in collab/rules directory
   - Integrate with existing workflows rather than creating new ones unnecessarily

## Operational Guidelines

### Repository Structure Management
- Maintain clean top-level directories (collab and output only)
- Use conventional commits with beautiful, descriptive messages
- Commit frequently using atomic commits
- Avoid git push operations - commit to local repository only

### Documentation Standards
- Include date/time headers with timezone in all markdown files
- Maintain change tracking/revision tables in all documents
- Keep changelogs in all source code files
- Follow "make it beautiful" rule for all documentation

### Development Workflow
- Use conventional commits (chore:, feat:, docs:, fix:, etc.)
- Follow project-specific rules from collab/rules directory
- Respect .env configurations for git attribution
- Use best practices for security, compliance, accessibility, and internationalization

## LLM Optimization Practices

### Prompt Engineering
- Structure requests to provide clear context from mounted AI home directory
- Use explicit, unambiguous language
- Break complex tasks into atomic operations
- Verify assumptions before executing operations

### Code Generation
- Follow established project patterns and conventions
- Maintain consistency with existing code style
- Add appropriate documentation and comments
- Consider maintainability and future extensions

### Error Handling & Verification
- Implement defensive programming practices
- Validate operations before execution
- Provide clear error messages and recovery options
- Run appropriate tests and quality checks

## Solo Entrepreneur Considerations

### Time Management
- Optimize for efficiency given 14+ hours daily AI usage
- Automate repetitive tasks where possible
- Provide quick wins while building long-term value
- Minimize context switching between projects

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

### Scalability
- Design solutions that work across multiple project contexts
- Use modular, reusable components
- Plan for increasing complexity as projects grow
- Maintain consistent interfaces across projects

## Best Practices Integration

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

### Quality Assurance
- Implement appropriate testing strategies
- Ensure code quality and maintainability
- Perform regular documentation updates
- Validate outputs against expected outcomes

### Performance Considerations
- Optimize for efficient processing
- Minimize resource usage where possible
- Consider impact on system performance
- Implement caching strategies when appropriate

## Communication Rules

1. **Collaboration Channel**: All communication should primarily occur through the collab/ directory
2. **Question Workflow**: Follow the strict workflow of questions -> proposals -> implementation
3. **Documentation**: Maintain comprehensive documentation for all significant operations
4. **Change Management**: Use proper version control and change tracking mechanisms

## Output Management

- The AI manages the output directory structure as needed
- Common pattern: output/tests/, output/docs/, output/code/, etc.
- Maintain clean separation between project-specific and shared resources
- Follow consistent naming conventions across projects

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# Change Tracking/Revision Table

| Date/Time            | Version | Description                                      | Author              |
|----------------------|---------|--------------------------------------------------|---------------------|
| 2025-10-24 10:50 CDT | 1.0.2   | Update date format consistency                   | Charles N Wyble (@ReachableCEO) |
| 2025-10-24 09:43 CDT | 1.0.1   | Standardize to change tracking table only        | 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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