3.0 KiB
3.0 KiB
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) andPM(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
Coderagent can pick up and execute. - Database Sync: Ensure all UI interactions correctly read/write to the
phase_dataorplanJSON 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, andstatus. - Backend Logging: Update the
app/api/mcp/route.tsemail.sendtool 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/NOTIFYevent bus (as defined inREALTIME_UPDATES.md). - Build the Next.js Server-Sent Events (SSE)
/api/projects/[projectId]/streamroute. - Wrap the Project layout with a
useProjectStreamhook 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 IDfor that project. - Code Injection: Ensure the AI agent automatically injects the Umami
<script>tag with the correct ID into the project's rootlayout.tsx. - UI Dashboard: Add an "Analytics" tab to the project workspace that surfaces the Umami traffic metrics natively inside Vibn.