How to Build and Deploy a Web App Without Writing Any Code

In this article, we're going to build and deploy a complete web application without writing a single line of code. And the best part, it's 100% free.

Planning the Application with AI

Every great project starts with a plan. We'll use the power of Gemini to create a detailed blueprint for our application. We begin with a detailed prompt, asking for an AI-powered notetaking web app built with modern technologies like React and TypeScript. We are also specifying several key features like a speech-to-text API, AI-powered summaries, grammar correction, and a world-class user interface.

Example Prompt: "Create a detailed technical and strategic plan for an AI-powered notetaking web app. The application should be built using React and TypeScript. Key features must include a speech-to-text API for voice notes, AI-driven summarization of long texts, integrated grammar correction, and a modern, world-class user interface."

With our prompt confirmed, Gemini's deep research gets to work, creating a comprehensive technical and strategic plan for our app. Once it's done, we can easily export it to Google Docs or download it as a PDF for our records.

Generating the Code with Google AI Studio

Now for the magic. We're heading over to Google AI Studio. We'll start a new project, telling the AI to build our note-taking app and, importantly, to use the detailed plan we just generated by uploading the PDF.

The code assistant then thinks through every step: designing the application scope, clarifying features, planning the technical details, and structuring the code. On the side, you can see it building the entire file structure for our React application.

And just like that, our app, "omnote," is ready to preview. Let's test the speech-to-text functionality.

Test Input: "Hi, hello."

Test Summary: The AI correctly identifies this as an informal greeting.

The core features are already working.

Adding New Features on the Fly

What if we want more? Let's ask the AI to add multiple templates. The assistant understands and immediately starts building the new components for checklists, image blocks, and a template selection screen. We can see the new to-do list option in the preview.

AI-Powered Debugging

Even AI-generated code can have bugs. Here, the assistant identifies an issue with a drawing library and suggests a fix. With the error resolved, our drawing feature is now fully functional. The AI has polished our app, adding a variety of useful templates to compete with other AI-powered note-taking apps.

Our application is complete and working perfectly. Now it's time to get it live on the internet.

Deploying the Application

Step 1: Download the Code

The first step is to download the code from AI Studio.

Step 2: Store the Code on GitHub

Next, head over to GitHub to store our code. We'll create a new private repository, name it notetake, and then simply unzip the file we just downloaded from AI Studio. Once it is unzipped, select that folder and add all files, preserving the original folder structure.

Step 3: Deploy with Vercel

For the final step, we'll use Vercel to deploy our app for free. After signing in with GitHub, we import our new repository.

Here's a crucial step: we need to add our Gemini API key as an environment variable to keep it secure. We'll copy the key from Google AI Studio, paste it into Vercel's environment variable settings, and hit deploy.

And that's it. Vercel is building our project. A few moments later, we get the congratulations message. Let's visit the link. And there it is. Our AI-powered notetaking app is live and fully functional for anyone to use.