agent-native-architecture

Agent-native architecture is a design approach where autonomous agents operate in prompt loops to achieve user-defined outcomes. It replaces manually scripted steps by turning UI features into agent-accessible capabilities using shared files, parity tooling, and prompt-driven guidance.

Design execution loops by implementing explicit completion signals, partial progress checkpoints, and context injection. Use shared files and action parity audits to ensure agents have the necessary atomic primitives and context.md files to reliably automate workflows without manual intervention.

Yes, CRUD parity tooling is required. Agent-native architecture relies on action parity audits to ensure every manual UI feature has matching agent-accessible capabilities, allowing autonomous agents to create, read, update, and delete resources through atomic primitives.

The best way is to review your UI actions and ensure corresponding parity tools exist. Document how agents reach feature goals using atomic primitives, prompt loops, and shared workspaces, enabling agents to replace manual workflows with emergent capabilities.

Handle approval flows and mobile sync by implementing mobile-friendly checkpoints and approval patterns. These mechanisms ensure adaptable, secure agent-native experiences by allowing users to review and validate autonomous agent actions during partial progress.

You should avoid agent-native architecture if your system requires strict deterministic step-by-step execution without autonomous decision-making. It is designed for emergent capability and composability, relying heavily on shared files and prompt-driven guidance rather than rigid scripting.