agent-native-architecture

Agent-native architecture is a design pattern where autonomous agents operate in a loop using atomic primitives and prompts. It codifies principles like parity, granularity, and composability to ensure robust, transparent automation within a shared workspace.

To design atomic tools for an autonomous agent loop, define granular primitives that empower flexible prompts to compose new features without code changes. This composability allows agents to handle open-ended requests by dynamically injecting context and evolving domain tools.

Yes, agent-native architecture supports safe self-modification workflows within a shared workspace. It enables agents to improve over time by allowing prompts to evolve with feedback while maintaining traceability and operating in the same data space as users.

The best way to achieve parity is to ensure every UI action has a corresponding agent tool and capability explicitly defined in prompts. This principle guarantees that agents can replicate user interactions transparently within the shared workspace.

You need a shared workspace for agent-native applications when real-time collaboration and traceability between agents and users are required. It allows both parties to operate in the same data space, enabling the agent to handle open-ended requests safely.

Yes, you can compose new features with prompts without code changes by leveraging the granularity and composability of atomic primitives. This approach allows features to emerge as outcomes described by prompts, enabling the agent to adapt dynamically.