The Major Editor provides a collaborative environment to modify your applications with AI assistance.

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Building with AI

The editor includes an AI assistant with full context of your application code. You describe what you want to build or change in the chat panel, and the AI reads your codebase, asks clarifying questions if anything is ambiguous, and works through the implementation with you.

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Images and Attachments

You can attach images and files to your AI chat messages. Drag and drop or paste screenshots, mockups, or reference images directly into the chat. Supported file types include:

• Images — PNG, JPG, GIF, and other common formats
• PDFs — for documentation or design references
• Text files — plain text files up to 100KB
• Markdown files — .md files up to 100KB
• JSON files — .json files up to 100KB

The AI uses these attachments as context when building or modifying your app — useful for matching a specific design, reproducing a bug from a screenshot, referencing documentation, or providing structured data for implementation.

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@ Mentions

Type @ in the chat to explicitly reference connectors, attachments, and workspace files in your message. This tells the AI exactly which resource or file you’re talking about.

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Tool Cards

When the AI executes resource operations in the chat, tool cards display the operation being performed. Each tool card shows:

• Tool name in plain text: The name of the tool being invoked, displayed as readable text.
• Tool description: A brief description of the tool appears below the tool name for clarity.
• Arguments with descriptions: Input parameters are labeled with human-readable descriptions and resolved resource names where applicable.
• Formatted output: Results are displayed with proper JSON formatting for clarity.

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Approvals & User Input

When your app requires approval before executing a tool or needs input from you, approval and ask-user cards render directly within the chat message flow. You no longer see separate overlay windows — everything stays in context within the chat. When an approval request or ask-user prompt is active, the chat input area switches to feedback mode:

• The input field becomes a response/feedback field for that specific request
• Toolbar actions are hidden to focus on the immediate decision
• Attachments are stashed temporarily and restored once the request is resolved

Respond directly in the input field to approve the action, provide feedback, or answer the question. Once resolved, the chat resumes normal operation and any stashed attachments are available again.

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Environment Variable Setup Requests

When the AI needs to set up environment variables, it sends a setup request that you can approve or decline. If you decline an environment variable setup request, you can include optional feedback explaining why. Your feedback is captured and sent back to the AI immediately via the control channel, and it also appears in the chat message history for future reference.

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Queued Messages

You can send follow-up messages while the AI is still working. Queued messages appear with a “Queued” label and a “Cancel” button. They are processed in order once the current task completes. You can cancel a queued message before it’s picked up. When you send a new message while the AI is waiting for your approval or decision, the pending decision is automatically interrupted and the agent resumes immediately with your new message.

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Plan Mode

When you send a request, the AI starts in Plan Mode — it analyzes your codebase and proposes a set of changes before touching any code. The plan appears in the Plan tab alongside Web, Code, and Logs. It includes a summary of what will change, which files are affected, and the implementation approach. From there you can approve the plan to let the AI start building, reject it to stay in Plan Mode with no changes made, or give feedback to have it revise. Once approved, the session switches to Accept Edits mode and you see changes appear in real-time in the code and preview panels.

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Preview & Inspection

Every editing session runs a live preview of your application in the right panel. As the AI makes changes, the preview updates automatically so you can verify behavior before committing. The panel includes three tabs:

• Preview — the running application, updated in real-time as changes are made
• Code — the generated source code for your application
• Log — runtime logs from the application, useful for debugging errors or verifying behavior

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Visual Selector

The visual selection tool lets you click elements in the preview to reference them in your AI chat. Hold Cmd (Mac) or Ctrl (Windows/Linux) to select multiple elements — each appears as a dismissible badge in the chat input. This is useful for telling the AI “change this button” or “fix the layout of these two components.” The preview’s URL bar shows all available routes as an autocomplete dropdown, making it easy to navigate your app.

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TypeScript Intelligence

The AI assistant has built-in TypeScript language server support, giving it precise code navigation across your codebase — go to definition, find references, and symbol lookup. This means the AI can understand your type relationships and imports accurately instead of relying on text search.

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Debugging with Production Logs

The AI assistant can query production logs from your deployed applications. Ask the AI to investigate runtime errors, search specific log patterns, or examine application behavior in production. The AI searches logs collected from your app’s container stdout and stderr, filtered by organization and app ID. Use this to debug issues in deployed apps without leaving the editor. The AI can correlate log messages with your code to identify root causes and suggest fixes.