docs: fix restoration of proposal artifacts with correct structure\n\n- Restore PROPOSAL-AGENTS.md with change tracking table moved to end\n- Restore README-PROPOSAL-AGENTS.md that was inadvertently deleted\n- Maintain single change tracking table format (no separate changelog)\n- Ensure all change tracking tables are positioned at document end\n- Keep previous version standards for consistency
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
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databank/collab/PROPOSAL-AGENTS.md
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# Date/Time
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Friday October 24, 2025 09:43 CDT (UTC-05:00)
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---
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---
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# PROPOSAL-AGENTS.md
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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.
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## Core Principles for AI Agents
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1. **Context Awareness**
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- Always acknowledge that you are operating within an AI home directory structure
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- Understand that this context is mounted across multiple project environments
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- Recognize that your operations may impact multiple interconnected projects
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2. **Communication Protocol**
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- Use the collab/ directory as the primary communication channel
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- Document decisions and changes in markdown files with proper revision tracking
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- Create structured proposals when suggesting significant changes
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3. **Project Context Integration**
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- Read project-specific documentation before beginning work
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- Respect project-specific rules found in collab/rules directory
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- Integrate with existing workflows rather than creating new ones unnecessarily
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## Operational Guidelines
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### Repository Structure Management
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- Maintain clean top-level directories (collab and output only)
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- Use conventional commits with beautiful, descriptive messages
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- Commit frequently using atomic commits
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- Avoid git push operations - commit to local repository only
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### Documentation Standards
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- Include date/time headers with timezone in all markdown files
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- Maintain change tracking/revision tables in all documents
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- Keep changelogs in all source code files
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- Follow "make it beautiful" rule for all documentation
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### Development Workflow
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- Use conventional commits (chore:, feat:, docs:, fix:, etc.)
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- Follow project-specific rules from collab/rules directory
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- Respect .env configurations for git attribution
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- Use best practices for security, compliance, accessibility, and internationalization
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## LLM Optimization Practices
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### Prompt Engineering
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- Structure requests to provide clear context from mounted AI home directory
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- Use explicit, unambiguous language
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- Break complex tasks into atomic operations
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- Verify assumptions before executing operations
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### Code Generation
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- Follow established project patterns and conventions
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- Maintain consistency with existing code style
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- Add appropriate documentation and comments
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- Consider maintainability and future extensions
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### Error Handling & Verification
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- Implement defensive programming practices
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- Validate operations before execution
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- Provide clear error messages and recovery options
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- Run appropriate tests and quality checks
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## Solo Entrepreneur Considerations
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### Time Management
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- Optimize for efficiency given 14+ hours daily AI usage
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- Automate repetitive tasks where possible
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- Provide quick wins while building long-term value
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- Minimize context switching between projects
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### Decision Making
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- Document reasoning for complex decisions
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- Consider impact across multiple projects
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- Maintain traceability for future reference
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- Suggest alternatives when appropriate
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### Scalability
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- Design solutions that work across multiple project contexts
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- Use modular, reusable components
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- Plan for increasing complexity as projects grow
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- Maintain consistent interfaces across projects
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## Best Practices Integration
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### Security Practices
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- Verify file permissions and access controls
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- Sanitize inputs and outputs appropriately
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- Protect sensitive information and credentials
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- Follow secure coding principles
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### Quality Assurance
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- Implement appropriate testing strategies
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- Ensure code quality and maintainability
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- Perform regular documentation updates
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- Validate outputs against expected outcomes
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### Performance Considerations
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- Optimize for efficient processing
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- Minimize resource usage where possible
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- Consider impact on system performance
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- Implement caching strategies when appropriate
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## Communication Rules
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1. **Collaboration Channel**: All communication should primarily occur through the collab/ directory
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2. **Question Workflow**: Follow the strict workflow of questions -> proposals -> implementation
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3. **Documentation**: Maintain comprehensive documentation for all significant operations
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4. **Change Management**: Use proper version control and change tracking mechanisms
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## Output Management
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- The AI manages the output directory structure as needed
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- Common pattern: output/tests/, output/docs/, output/code/, etc.
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- Maintain clean separation between project-specific and shared resources
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- Follow consistent naming conventions across projects
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---
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# Change Tracking/Revision Table
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| Date/Time | Version | Description | Author |
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|----------------------------------|---------|--------------------------------------------------|---------------------|
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| 2025-10-24 09:43 CDT (UTC-05:00) | 1.0.1 | Standardize to change tracking table only | Charles N Wyble (@ReachableCEO) |
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| 2025-10-24 09:43 CDT (UTC-05:00) | 1.0.0 | Initial proposal for baseline AGENTS.md | Charles N Wyble (@ReachableCEO) |
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---
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194
databank/collab/README-PROPOSAL-AGENTS.md
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194
databank/collab/README-PROPOSAL-AGENTS.md
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# 🤖 README-PROPOSAL-AGENTS.md
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> Beautiful documentation for AI Agent Guidelines Proposal
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---
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## 📋 Table of Contents
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- [Overview](#overview)
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- [Proposal Structure](#proposal-structure)
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- [Key Features](#key-features)
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- [Implementation Guide](#implementation-guide)
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- [Best Practices](#best-practices)
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---
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## 🧠 Overview
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Welcome to the beautifully designed documentation for the **PROPOSAL-AGENTS.md** file. This document outlines a comprehensive baseline for AI agent operations that can be mounted across all your projects via your AI home directory.
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| **Attribute** | **Details** |
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|---------------|-------------|
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| **Purpose** | Baseline AI agent guidelines for all projects |
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| **Target User** | Solo entrepreneur (Founder/CTO/Operations) |
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| **AI Usage** | Optimized for 14+ hours daily interaction |
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| **Structure** | Mountable across multiple project environments |
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---
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## 🏗️ Proposal Structure
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```
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┌─────────────────────────────────────────────────────────────┐
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│ PROJECT ENVIRONMENT │
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├─────────────────────────────────────────────────────────────┤
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│ ┌─────────────────┐ ┌─────────────────────────────────┐ │
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│ │ │ │ │ │
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│ │ PROJECT-SPECIFIC│ │ 🏠 AI HOME DIRECTORY │ │
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│ │ CONTEXT │ │ (Mounted Volume) │ │
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│ │ │ │ │ │
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│ │ - Project docs │ │ - AGENTS.md (base rules) │ │
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│ │ - Codebase │ │ - PROPOSAL-AGENTS.md │ │
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│ │ - Requirements │ │ - Documentation Standards │ │
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│ └─────────────────┘ │ - Operational Guidelines │ │
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│ │ - LLM Optimization Practices │ │
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│ └─────────────────────────────────┘ │
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└─────────────────────────────────────────────────────────────┘
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```
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### 📁 File Location
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```
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AI-Home-Directory/
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├── collab/ # Collaboration directory
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│ └── proposals/ # Proposals subdirectory
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│ ├── PROPOSAL-AGENTS.md # Baseline agent guidelines
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│ └── README-PROPOSAL-AGENTS.md # This beautiful file
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```
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---
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## ✨ Key Features
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### 🎯 Core Principles for AI Agents
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| Principle | Description |
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|-----------|-------------|
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| **Context Awareness** | Understand the mounted AI home directory across projects |
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| **Communication Protocol** | Use collab/ directory as primary channel |
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| **Project Integration** | Respect project-specific rules and workflows |
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### ⚙️ Operational Guidelines
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- **Repository Management**: Clean structure with conventional commits
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- **Documentation Standards**: Date/time headers, revision tracking
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- **Workflow Adherence**: Follow question -> proposal -> implementation
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### 🧩 LLM Optimization Practices
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- **Prompt Engineering**: Clear, structured requests
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- **Code Generation**: Consistent with project patterns
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- **Error Handling**: Defensive programming approach
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---
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## 📊 Implementation Guide
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### Step 1: Understanding the Framework
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1. **Read Project Context** → Always review project-specific documentation first
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2. **Respect Existing Rules** → Check collab/rules directory for project-specific guidelines
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3. **Integrate with Workflow** → Follow established patterns rather than creating new ones
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### Step 2: Following Documentation Standards
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- [ ] Include date/time header with timezone
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- [ ] Maintain change tracking/revision table
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- [ ] Create changelog in source files
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- [ ] Apply "make it beautiful" rule to all documentation
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|
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### Step 3: Operational Excellence
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- [ ] Use atomic commits with conventional commit messages
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- [ ] Commit frequently to local repository
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- [ ] Avoid git push operations (as per guidelines)
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- [ ] Maintain clean top-level directory structure
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---
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## 🏆 Best Practices
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### 🛡️ Security Practices
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- 🔐 Verify file permissions and access controls
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- 🛡️ Sanitize inputs and outputs appropriately
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- 🔐 Protect sensitive information and credentials
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- 🔒 Follow secure coding principles
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### 📈 Quality Assurance
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- ✅ Implement appropriate testing strategies
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- ✅ Ensure code quality and maintainability
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- ✅ Perform regular documentation updates
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- ✅ Validate outputs against expected outcomes
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### ⚡ Performance Considerations
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- ⚡ Optimize for efficient processing
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- 💾 Minimize resource usage where possible
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- 📊 Consider impact on system performance
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- 🔄 Implement caching strategies when appropriate
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---
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## 🚀 Solo Entrepreneur Optimization
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For someone using AI 14+ hours daily with multiple projects:
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| Need | Solution |
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|------|----------|
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| **Time Efficiency** | Atomic operations, quick wins |
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| **Context Switching** | Consistent interfaces across projects |
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| **Decision Documentation** | Clear reasoning trails for complex decisions |
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| **Multi-Project Impact** | Considerations for interconnected projects |
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---
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## 🤝 Communication Workflow
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```
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┌─────────────┐ ┌──────────────┐ ┌─────────────────┐
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│ Question │ -> │ Proposal │ -> │ Implementation │
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│ │ │ │ │ │
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│ What to do? │ │ How to do it?│ │ Execute & Test │
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└─────────────┘ └──────────────┘ └─────────────────┘
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```
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### Primary Channels
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- **Collaboration**: Use collab/ directory for all communication
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- **Documentation**: Maintain comprehensive records
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- **Change Management**: Use version control with proper tracking
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---
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## 💼 Founder/CTO Specific Considerations
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### Decision Making Framework
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- 📊 Document reasoning for complex decisions
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- 🔗 Consider impact across multiple projects
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- 📜 Maintain traceability for future reference
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- 🔄 Suggest alternatives when appropriate
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|
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### Scalability Planning
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- 🏗️ Design solutions that work across multiple project contexts
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- 🧱 Use modular, reusable components
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- 📈 Plan for increasing complexity as projects grow
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- 🔗 Maintain consistent interfaces across projects
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---
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## 📈 Active Development Status
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> 🔄 **Note**: This proposal is part of a living knowledge base that supports your 14+ hours daily AI usage.
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### Current Focus Areas
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- [x] Documentation standards
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- [x] Operational guidelines
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- [x] LLM optimization
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- [ ] Integration patterns (planned)
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- [ ] Performance metrics (planned)
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---
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## 📞 Getting Help
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For questions about implementing these guidelines:
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1. Create a new issue in the collab/ directory
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2. Reference this proposal document
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3. Provide specific context about your use case
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4. Follow the established question -> proposal -> implementation workflow
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---
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*Last updated: October 24, 2025*
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*Part of the AIOS (AI Operating System) ecosystem*
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*Optimized for solo entrepreneur workflows*
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Reference in New Issue
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