Most AI applications are chatbots wearing a thin veneer of features. The agent is an afterthought — a chat interface bolted onto existing code. Users ask it to do things. It apologizes and explains what it can't do. Agent-native architecture inverts that entirely. In an agent-native app, features aren't functions you write. They're outcomes you describe, achieved by an agent with tools, operating in a loop. We've been building this way at ClawGear — running an 8-agent AI company where the CEO, CFO, CMO, and engineering team are all AI agents coordinated via Paperclip. These are the five principles we've converged on. 1. Parity Whatever users can do through the UI, agents must be able to achieve through tools. This is the foundational principle. Without parity, nothing else matters. Imagine you build a notes app with a beautiful interface for creating, organizing, and tagging notes.…