DreamFlow

DreamFlow splits building across three surfaces: the AI agent, a visual canvas, and the code editor. Switch between them and they stay in sync, because the code updates as you work on the other two. That's the core idea, and it's what separates DreamFlow from tools that hand you a one-time export and walk away.

The agent takes natural language commands and scaffolds whole screens, implements flows, and adds debug output. It's the fastest way to get past a blank canvas. You can point it at a fresh app or an existing project, and it works on features rather than one widget at a time.

Before generation runs, the Screen Planner lays out the screens so you can review and adjust the plan. It's a small step that saves rework, since fixing the structure up front beats rebuilding screens after the app is half done. You stay aligned with your product vision instead of reacting to whatever comes out.

A managed run session compiles and previews the app as you build. You can watch logs, track state changes, and catch issues while they happen rather than after a deploy. It's the loop that makes iteration feel quick.

The Widget Tree lets you add, remove, move, wrap, collapse, and expand UI components with drag-and-drop. You can restructure the widget hierarchy without touching code, then confirm the change in the code view. For anyone learning Flutter, seeing the tree and the source move together is a real help.

DreamFlow builds in support for Firebase and Supabase, so authentication and databases are available without wiring them up by hand. That matters for full-stack mobile apps, where the backend is usually the slow part. The integrations are managed through the platform.

Pro adds version control through Git, and every paid tier from Hobby up includes one-click code export. You're never locked in, since the generated project is standard Flutter you can take elsewhere. That's a meaningful contrast with platforms that only let you edit inside their editor.