Building an AI-Powered App with Next.js, Tailwind CSS, and OpenAI API

Recently, I built an AI-powered web application using Next.js, Tailwind CSS, and the OpenAI SDK. Here’s a breakdown of the development steps and tools I used.

🔧 Setup & Installation

I started by creating a new Next.js app using the following command:

npx create-next-app@latest out-app

During setup, I selected:

✅ Tailwind CSS: Yes
✅ App Router: Yes
✅ Use /src directory structure: Yes
✅ Default options for other settings

This gave me the latest App Router structure under src/app.

🧪 Running the App

To launch the development server:

cd out-app
npm run dev

🧠 Installing OpenAI SDK for AI Features

I installed the official AI SDK for seamless OpenAI integration:

npm install ai @ai-sdk/openai

These packages allow powerful AI interactions within the app. More details on AI with Vercel can be found at:

🌐 Next.js
🤖 Vercel AI SDK

📁 Creating the API Route

Inside the src/app/api/ folder, I created a new route to interact with OpenAI's API. This route handles server-side requests to generate completions from the OpenAI Assistants API.

🪝 Using `useCompletion` Hook

On the client side, I used the useCompletion hook from the SDK:

const { completion, handleSubmit, input, setInput } = useCompletion({
  api: "/api/chat",
});

This hook simplifies interaction with the API and handles all the request/response logic behind the scenes.

🧠 Why This Stack?

Next.js provides SSR, App Router, and seamless deployment with Vercel.
Tailwind CSS helps build UI faster with utility classes.
OpenAI SDK brings powerful language understanding to the frontend with minimal setup.

🛠️ Bonus: My Background with AI & APIs

I’ve previously worked on:

🔧 Building bots and automation systems using Python
☁️ Integrating with AWS and deploying cloud-native solutions
📡 Developing REST APIs
💻 Using JavaScript for frontend/backend logic
🤖 Creating custom workflows using the OpenAI Assistants API

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