master-ai/vibn-frontend/docs/todo/NEXT_STEPS.md

Vibn Product Roadmap & To-Do List

This document tracks the immediate next steps for the Vibn UI and project management features.

1. Complete the "Plan" UI

Status: Pending

The Plan UI needs to be the central hub where founders and AI agents collaborate on the product roadmap, user stories, and architecture.

Key Tasks:

• Visual Design: Implement the UI for viewing and editing the PRD (Product Requirements Document).
• Agent Integration: Ensure the Atlas (PRD) and PM (Product Manager) agents can seamlessly update the plan and reflect changes in the UI in real-time.
• Task Management: Build out the interface for tracking actionable tasks (e.g., KanBan or List view) that the Coder agent can pick up and execute.
• Database Sync: Ensure all UI interactions correctly read/write to the phase_data or plan JSON structure in the Postgres database.

2. Build the "Messages/Inbox" UI

Status: Pending

Projects need a dedicated "Messages" tab to act as a unified inbox for all external communications, specifically emails sent by the AI or the platform.

Key Tasks:

• Email History Table: Create a Postgres table (e.g., project_messages) to log every email sent via the new Mailgun integration. The schema should include: project_id, to, subject, body_text, body_html, sent_at, and status.
• Backend Logging: Update the app/api/mcp/route.ts email.send tool to insert a record into this new table immediately after a successful Mailgun dispatch.
• UI Implementation: Build a clean Inbox UI within the Project Dashboard.
  • List view of all sent/received messages.
  • Detail view to read the actual email content (rendering the compiled HTML/MJML safely).
  • (Future) Webhook integration with Mailgun to receive replies and log them in this same UI.

3. Implement System-Wide Real-Time UI Updates

Status: Pending

Key Tasks:

• Implement the Postgres LISTEN/NOTIFY event bus (as defined in REALTIME_UPDATES.md).
• Build the Next.js Server-Sent Events (SSE) /api/projects/[projectId]/stream route.
• Wrap the Project layout with a useProjectStream hook so SWR automatically re-fetches when the background AI modifies the database (e.g., checking off tasks, editing the PRD).

4. Integrate Open-Source Analytics (Umami)

Status: Pending

Every project deployed by Vibn should automatically have privacy-first analytics injected and visible to the founder.

Key Tasks:

• Infrastructure: Deploy Umami via Coolify using Docker Compose (backed by the existing Postgres DB).
• Automation: Build a backend integration so when an AI ships a project, Vibn programmatically calls the Umami API to generate a unique Website ID for that project.
• Code Injection: Ensure the AI agent automatically injects the Umami <script> tag with the correct ID into the project's root layout.tsx.
• UI Dashboard: Add an "Analytics" tab to the project workspace that surfaces the Umami traffic metrics natively inside Vibn.