Personal AI Infrastructure

PAI is an ambitious project to create a personal AI operating system that serves as your intelligent assistant for software development and daily tasks. My implementation follows directly from Daniel Miessler’s PAI project. If you have not read or followed any of his work, I highly recommend you check it out.

Overview

The system is built around Claude Code and extends it with:

• Skills System: Self-contained domain expertise packages that can be loaded on demand
• Hooks: Event-driven automation scripts that respond to various triggers
• Agents: Specialized AI personalities for different types of tasks

Architecture Highlights

CLI-First Design

Everything in PAI follows the principle of “Code Before Prompts” - deterministic CLI tools that can be orchestrated by AI:

// Example: A skill workflow notification
${PAI_DIR}/tools/skill-workflow-notification WorkflowName CORE

Progressive Context Loading

PAI uses a 3-tier context loading system for token efficiency:

1. Tier 1: System prompt with skill descriptions
2. Tier 2: SKILL.md files with main reference material
3. Tier 3: Deep-dive reference files loaded on demand

Key Features

• Parallel Agent Execution: Spawn multiple agents to work on tasks concurrently
• Automatic History Capture: All work is automatically documented and preserved
• Security-First: Multiple security checks and prompt injection defenses
• Voice Integration: Optional voice feedback system for notifications

What I Learned (to date)

Building PAI taught me a lot about:

• Designing systems for AI interaction
• Managing context windows efficiently (or not)
• Building/ using CLI tools in TypeScript
• Event-driven architecture patterns
• Anthropic’s Claude subscription tiers and billing limits
• Git/ GitHub and basic system engineering processes

This project is one of my attempts to learn and mature my understanding for how humans and AI can work together more effectively.