se-agent-native-architecture

Agent-native architecture is a software design pattern where agents act as first-class participants in execution loops. You need it when building autonomous agents, MCP tools, or self-modifying apps that require dynamic context injection and minimal hard-coded workflows.

To build autonomous agents, define atomic tools, write a guiding system prompt, and run an agent loop that iterates until the task is complete. This approach uses dynamic context injection and composability to handle open-ended tasks instead of relying on hard-coded workflows.

Parity ensures every UI action has a corresponding agent tool, enabling seamless handoff between human and agent. This architecture allows both to operate on the same atomic primitives within a shared workspace, maintaining continuous learning and collaboration.

Agent-native architecture explicitly plans for edge cases, resume operations, and safety checks within its execution loop. It enforces tooling primitives and prompt-based behavior to ensure autonomous agents operate safely in production workloads.

The best way to design MCP tools is to keep primitives atomic and define features as descriptions in prompts that compose into complex tasks. This granularity combined with a single shared data space enables agents to dynamically inject context and handle open-ended tasks.