How to vibe codeGorgias

Prerequisites

• Node.jsfree

  Runtime environment for Next.js full-stack development

• GitHubfree

  Version control and deployment pipeline integration

• Supabase Accountfree

  Managed Postgres database with realtime capabilities and vector support

AI coding tools

• Claude Code

  Best-in-class multi-file agentic coding tool for scaffolding full-stack features and fixing complex webhook handlers

• Cursor

  Ideal for fine-tuning UI components, chat interfaces, and reviewing code diffs interactively

Build guide

1. 01Project Scaffolding and Database Schema

   Initialize the Next.js project with Tailwind CSS, shadcn/ui, and configure Supabase with tables for tickets, messages, customers, and store orders.

   Initialize a Next.js project with TypeScript, Tailwind CSS, and App Router. Set up Supabase client connections and create a robust database schema using SQL migrations for: 'tickets' (id, customer_id, status, channel, assignee, created_at), 'messages' (id, ticket_id, sender_type, body, raw_payload), 'customers' (id, email, name, external_store_id), and 'orders' (id, customer_id, total_price, fulfillment_status, line_items). Ensure proper foreign key constraints, indexes on ticket status and customer email, and configure better-auth for secure user authentication.

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2. 02Unified Helpdesk Inbox UI

   Build a multi-pane agent workspace interface featuring a ticket list view, active conversation thread, and a context sidebar.

   Create a responsive multi-pane dashboard layout mimicking a customer support helpdesk. Build a left sidebar for filtering tickets by status (open, pending, closed) and channel (email, chat, widget). Build a central conversation thread view that renders chronological messages with avatars, formatting, and a rich text reply box. Build a right-hand collapsible customer sidebar that displays live customer details, order history, and past support tickets fetched from the Supabase database. Use Tailwind CSS and shadcn/ui components.

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3. 03Webhook Ingestion Pipeline

   Implement API route endpoints to receive incoming messages from external channels and webhooks.

   Implement secure API webhook route handlers in Next.js to ingest incoming customer interactions. Create an endpoint '/api/webhooks/messages' that parses incoming payloads, matches sender emails to existing customer records in Supabase (or creates a new customer), automatically generates a new ticket if none is active, and stores the message. Implement Supabase Realtime subscriptions on the frontend so the inbox updates instantly when new webhook events arrive without manual page refreshes.

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4. 04Store API Integration and Mutating Actions

   Build backend integrations to fetch store data and execute side-effect actions like order cancellation and discounting directly from the UI.

   Build a service layer that communicates with an e-commerce platform REST API (or a mock store API simulating Shopify). Implement functions to fetch order details, issue refunds, cancel orders, and apply discount codes. Expose these as backend API routes secured by agent authentication. Build UI action buttons directly into the agent workspace ticket sidebar that trigger these server actions, handle loading states, display success/error toasts, and append an internal note to the ticket timeline documenting the mutation.

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5. 05Autonomous AI Agent & RAG Pipeline

   Integrate the Anthropic API with vector search to power an autonomous assistant that answers customer questions using store data and policies.

   Implement an AI Agent pipeline using the Anthropic API and Supabase pgvector for Retrieval-Augmented Generation (RAG). Create an ingestion script that chunks and embeds store policy documents and product catalogs into a vector table. When an incoming customer chat message arrives, query the vector database for relevant context, construct a strict system prompt enforcing brand guardrails and policy constraints, and call the Claude model. If the query requires an automated action (like order status lookup), use tool-calling definitions to securely fetch order data and return the resolution automatically or escalate to a human agent.

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6. 06Analytics Dashboard and Polish

   Add performance reporting dashboards, ticket tagging, macros, and final styling refinements.

   Build a reporting dashboard view that calculates key support metrics from database records: total ticket volume, average first response time, resolution rate, and revenue attribution generated via support interactions. Implement canned response macros that insert predefined text and automatically trigger order updates. Add error boundaries, toast notifications, loading skeletons, and write comprehensive test suites for core ticket routing and AI tool-calling workflows.

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