Case Study: Building Note Sync Pro with Next.js, Convex, and Gemini AI

The Vision: A Modern, AI-Powered Blogging Experience

For my "Note Sync Pro" project, I wanted to build more than just a standard blog. The goal was to create a seamless, modern writing platform that leverages the best of a full-stack TypeScript environment, a real-time database, and the creative power of generative AI.

The core vision was to build a platform where writers could not only manage their content effortlessly but also get assistance from an AI to enhance their creative process, from generating ideas to refining their tone.

Core Technologies

• Framework: Next.js (App Router)
• Database & Backend: Convex (Real-time serverless backend)
• AI Integration: Google Gemini via the Vercel AI SDK
• Text Editor: Plate.js (A rich text editor framework for React)
• Image Uploads: UploadThing
• Authentication: Custom JWT-based system
• Styling: Tailwind CSS with shadcn/ui

Key Challenge: Seamless AI & Real-Time Data Integration

The primary challenge was to tightly integrate the AI writing assistant directly into the rich text editor while ensuring the entire application state remained synchronized in real-time. A user should be able to trigger an AI action, see the generated content stream directly into the editor, and have it save instantly without a manual "save" button.

My Solution: A Reactive, Serverless Architecture

1. Convex for the Real-Time Backend

Convex was the perfect choice for this. It is a serverless platform that provides a real-time database out of the box. Instead of building a traditional REST or GraphQL API, I wrote my backend functions (called "mutations" and "queries") directly in TypeScript, and Convex handled the rest.

When a user types in the Plate.js editor, a Convex mutation is called to update the document. Convex then automatically pushes the updated state to all connected clients, ensuring perfect synchronization.

// A simplified Convex mutation for updating a post
import { mutation } from './_generated/server';
import { v } from 'convex/values';
 
export const updateContent = mutation({
  args: {
    postId: v.id('posts'),
    content: v.string(),
  },
  handler: async (ctx, args) => {
    // Authentication check would go here
    await ctx.db.patch(args.postId, { content: args.content });
  },
});

2. Vercel AI SDK for Streaming AI Responses

To make the AI feel truly integrated, I used the Vercel AI SDK. When a user prompts the AI assistant, a server-side Next.js API route is called. This route communicates with the Google Gemini API and streams the response back to the client.

The useCompletion hook from the SDK makes it incredibly easy to handle this stream on the frontend and update the editor in real-time as the AI "thinks."

// Simplified example of the AI trigger in the React component
'use client';
import { useCompletion } from 'ai/react';
 
function AiWritingAssistant({ editor }) {
  const { completion, complete } = useCompletion({
    api: '/api/generate', // Next.js API route
  });
 
  const handleGenerate = () => {
    const prompt = 'Summarize the following text: ...';
    complete(prompt);
  };
 
  // This effect would stream the 'completion' text into the editor
  // ...
 
  return <button onClick={handleGenerate}>Generate Summary</button>;
}

What I Learned

• The Power of a True Full-Stack Framework: Convex allowed me to stay in a TypeScript-only environment for both frontend and backend logic, dramatically increasing development speed.
• Streaming is Key for AI UX: For generative AI features, streaming the response token-by-token is non-negotiable. It provides instant feedback and makes the application feel alive and responsive.
• Component-Based Editors are the Future: Using a framework like Plate.js, which is built on top of Slate.js, gives you granular control over the editor's behavior, making complex integrations like this possible.

Note Sync Pro was a challenging but incredibly rewarding project. It pushed my skills in building complex, interactive, and intelligent web applications and demonstrated the immense potential of combining modern serverless backends with generative AI.