agent-native-architecture

Agent-native architecture is a software design approach where autonomous agents act as primary functional units to achieve features as outcomes. You need it when building self-modifying applications or autonomous systems driven by LLMs.

To design tools for autonomous systems, build primitive tools ensuring CRUD completeness for entities and handle dynamic capability discovery. This allows LLM agents to interact with other tools and manage tasks autonomously.

The best way to manage shared workspaces for autonomous agents is using files as a universal interface. This pattern allows agents to organize files, interact with other tools, and manage tasks autonomously.

Execution patterns handle context limits in agent-driven software by using completion signals and partial completion for resume capabilities. This ensures autonomous systems maintain functionality despite context window constraints.

Yes, you can use prompt engineering to test agent-native applications by applying specific testing methodologies. This involves refining system prompts and context injection to validate that agents achieve user-defined outcomes.