agent-native-architecture

Agent-native architecture centralizes behavior in prompts and atomic tools rather than hardcoded logic. Dynamic context injection feeds live application state into system prompts, enabling agents to act on current data by reading a shared context file at session start.

To build an autonomous agent, define minimal atomic primitives like read_file, write_file, list_files, and bash. Craft a system prompt describing tool usage, establish a shared workspace, and run the agent in a loop to observe and refine its tool calls.

Prompt-driven orchestration ensures UI actions map to agent capabilities by enforcing parity between the interface and atomic tool primitives. This composability allows gradual domain-tool graduation and safe prompt-driven evolution when appropriate.

No specific frameworks are required. You need a shared workspace like a Documents directory, a context.md file for session initialization, and a minimal set of atomic primitives including read_file, write_file, list_files, and bash to start building.

Refine agent judgment criteria by adjusting the system prompt during the observation loop. Centralizing behavior in prompts allows you to modify tool usage instructions and decision rules without altering the underlying atomic tool primitives.

Prompt-driven evolution enables self-modification when appropriate by allowing the agent to adjust its behavior through updated system prompts. This leverages composability and safety constraints to ensure gradual domain-tool graduation within defined boundaries.