Agents: Inner Loop vs Outer Loop
Explains the difference between an AI agent's inner loop (verifying work within a task) and outer loop (learning across tasks).
Explains the difference between an AI agent's inner loop (verifying work within a task) and outer loop (learning across tasks).
Explains the core concepts of AI coding agents (rules, commands, skills, etc.) and provides a unified mental model for understanding them.
Proposes a new AI agent architecture based on Alfred North Whitehead's process philosophy, treating agents as dynamic processes rather than static entities.