agent-native: what it is, what problem it solves & why it's gaining traction

What it solves

Agent-Native provides a framework for building "agent-native" applications where AI agents are not just chat interfaces on the side, but are deeply integrated into the app's core functionality. It solves the problem of bridging the gap between raw AI agents and polished SaaS products by allowing agents and UIs to share the same state, database, and actions.

How it works

The framework treats the agent and the UI as equal citizens. It uses a system of "Actions"—defined once and usable across the UI, agent, API, MCP, and CLI. It provides a runtime that includes tools, skills, memory, and observability, while remaining backend-agnostic, allowing developers to plug in any Nitro-compatible host and Drizzle-supported SQL database.

Who it’s for

It is designed for developers building product-grade agentic software, SaaS applications, or those wanting to add advanced agent capabilities (like visual planning and PR recaps) to existing coding agents such as Cursor, GitHub Copilot, or Claude Code.

Highlights

• Unified Actions: Define a single action that can be triggered by a user click, an AI prompt, or an API call.
• Shared State: Real-time synchronization between the human user and the agent using a single database.
• Agent-to-Agent (A2A): Capability for agents to tag and coordinate with other agents.
• Extensible Skills: Ability to add specific capabilities, such as /visual-plan and /visual-recap, to external AI coding tools via a simple command.
• Template Gallery: Includes a variety of open-source SaaS templates (e.g., analytics, slides, design prototyping) to jumpstart development.