agent-native-architecture

Agent-native architecture is a design approach where autonomous agents are first-class citizens, enabling emergent capabilities and self-improving characteristics. It relies on core principles like Parity, Granularity, and Composability to structure applications for robust operation.

To design an autonomous agent system from scratch, apply a framework covering core principles, architecture patterns, and tool design. Implement event-driven architectures, shared workspaces, and approval gates to ensure scalable and robust autonomous operation.

Architecture patterns for autonomous systems include event-driven architectures, shared workspaces, and approval gates. These patterns support autonomous operation by managing how agents interact with their environment and execute tasks safely.

Design tools for LLM agents by creating primitive, atomic tools that perform single, well-defined tasks. Introduce domain-specific tools only when necessary to abstract complexity and enhance the autonomous system's emergent capabilities.

Yes, you can refactor an existing codebase into an agent-native application. The framework provides testing and refactoring practices to transition software design toward autonomous operation and integrate agents as first-class citizens.

Introduce primitive, atomic tools as the default in autonomous systems to maintain flexibility. Introduce domain-specific tools when you need to abstract repetitive complex operations, balancing the agent's emergent capability with targeted efficiency.