agent-native-architecture

Agent-native architecture orchestrates agents through atomic primitives and prompt-defined outcomes. It shifts development from hard-coded workflows to dynamic prompt-driven tools that mirror UI actions, enabling transparent and adaptable automation.

You build applications with parity by using atomic tool primitives that mirror UI actions. Describe a user goal in natural language and let the agent plan and execute tasks by looping through these atomic tools until completion.

Yes, prompt-driven workflows support dynamic context injection that adapts to current data and app state. The architecture includes mobile checkpoint and resume capabilities, allowing offline degradation and composable prompts for emergent capability.

Agent-native architecture ensures safe, auditable agent behavior through explicit completion signals and checkpoints. It provides clear parity and governance guidance to support safe evolution of automated workflows.

The best way to transition is adopting a prompt-driven architecture with atomic tool primitives. This approach replaces rigid hard-coded workflows with modular prompts that adapt to current data, enabling composable and transparent automation.

You should avoid prompt-driven agent orchestration when your workflows require rigid hard-coded processes without adaptability. If your application state lacks clear data injection points or does not support checkpoint and resume capabilities, this architecture is unsuitable.