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# Development

AppKit provides multiple development workflows to suit different needs: local development with hot reload, AI-assisted development with Agent Skills, and remote tunneling to deployed backends.

## Prerequisites

- [Node.js](https://nodejs.org) v22+ environment with `npm`
- Databricks CLI (v0.295.0 or higher): install and configure it according to the [official tutorial](https://docs.databricks.com/aws/en/dev-tools/cli/tutorial).
- A new Databricks app with AppKit installed. See [Bootstrap a new Databricks app](../index.md#quick-start-options) for more details.

## Development flows

There are multiple supported development flows available with AppKit:

1. **[Local development](./local-development.mdx)**: Run the development server with hot reload for both UI and backend code. This is the default development flow and is suitable for most use cases.
2. **[AI-assisted development](./ai-assisted-development.mdx)**: Use an AI coding assistant with Agent Skills to explore data, run CLI commands, and scaffold your app interactively.
3. **[Remote Bridge](./remote-bridge.mdx)**: Create a remote bridge to a deployed backend while keeping your queries and UI local. This is useful for testing against production data or debugging deployed backend code without redeploying your app.

## See also
 
- [App management](../app-management.mdx): Manage your AppKit application throughout its lifecycle using the Databricks CLI
- [Architecture](../architecture.md): Learn about the architecture of AppKit