ia-agent-native-architecture

Agent-native architecture design is the process of planning systems where agents replace UI users as the primary actor for MCP tools, requiring parity, composability, and verifiable execution. You need it when building agent-loop systems with shared workspaces.

To design an MCP tool-driven architecture, define tool granularity, system prompts, and context injection patterns, then validate the plan using an architecture review checklist covering hooks governance, security boundaries, and completion signals.

Yes, agent-native design requires hooks governance and security approval gates to ensure safe execution. Architecture principles dictate validating security boundaries and automating governance through hooks before implementing self-modifying agent systems.

The best way to test agent-native systems is applying architecture principles to establish testing criteria that validate execution parity, durable context patterns, and completion signals before deployment.

Yes, you can use shared workspace file patterns for context injection in agent-loop architectures. Agent-native design principles route to reference sections covering workspace interfaces, durable context patterns, and prompt engineering.

Brittle agent workflows fail due to poor parity and lack of verifiable execution. Composability fixes them by applying agent-native architecture principles that ensure tools, shared workspaces, and context injection achieve verifiable execution.