agent-native-architecture

Agent-native architecture lets autonomous agents drive outcomes by looping over primitive tools, whereas prompt-native design relies on explicit text instructions. It ensures UI parity so agents can perform all user actions through tool-based workflows.

To design an agent-native system, you define a minimal agent loop using primitive tools to achieve user-facing outcomes. This requires applying UI parity, dynamic context injection, and a unified orchestrator across multiple agent types.

The best way to orchestrate multi-agent workflows is using a unified orchestration framework with built-in safety rails and explicit approval steps. This approach separates prompts, tools, and orchestration for reliable agent execution.

You ensure UI parity by providing consistent capability coverage through tool-based actions. This means designing primitive tools that map directly to user-visible actions, allowing agents to interact with the application just like a human user would.

Yes, a unified orchestrator is required to manage multiple agent types effectively. It coordinates the agent loop, handles context injection, and enforces safe approvals, ensuring that autonomous agents produce reliable user-visible results.

You should avoid an agent-native approach if your application cannot support explicit prompts, safe approvals, and primitive tool loops. Without a unified orchestration framework, autonomous agents may fail to produce reliable user-visible outcomes.