Starting a new software project can feel like standing at the bottom of a mountain. You know what you want to build, but before you can write the first line of unique code, you have to tackle the boilerplate: setting up the project structure, installing dependencies, configuring build tools, and integrating frameworks. It’s a necessary but often tedious process that consumes valuable time and energy.
But what if you could skip most of that? What if you could describe your goal in plain English and have an AI assistant lay the entire foundation for you?
We decided to put that idea to the test using Gemini Code Assist, Google's AI-powered collaborator for developers. We recorded the entire process, and the results were stunning. In just over 90 seconds, we went from an empty folder to a functional web application, all driven by a single prompt.
Here’s how it happened.
We started inside the VS Code editor with a completely empty project. No files, no folders, nothing. We opened the Gemini Code Assist chat and gave it a simple, high-level instruction:
Create a simple web app to track orders.
Instead of immediately spitting out a wall of code, Gemini did something refreshingly thoughtful: it made a plan. It outlined its approach, ensuring we were aligned before it proceeded.
Here was the proposed plan:
Project: Planning Order Tracker App
Technology: Use React and Bootstrap for styling.
Core Features:
A main page to display a list of all orders.
Each order in the list will show its ID, customer name, and current status.
Data will start as a simple, hardcoded list of orders.
The structure will be set up to easily allow for future updates to order statuses.
This approach is fantastic. It confirms the technology stack and scope, giving the developer a clear "Should I proceed?" checkpoint. We agreed, and Gemini got to work.
With our "Yes," Gemini began executing the plan.
First, it generated and ran the shell command to create a new React application, instantly building the project directory and all the necessary starter files.
npx create-react-app order-tracker
Next, it moved to install the Bootstrap styling library. And here, something fascinating happened. The AI made a minor mistake—it initially tried to run the installation command in the parent directory, not inside the new project folder it had just created.
But before we even had a chance to correct it, Gemini caught its own error.
It sent a message: "My apologies, I made a mistake in the previous command. I'll correct the path and install Bootstrap in the order-tracker directory."
This moment was a powerful demonstration of the tool's capability. It’s not just a blind code generator; it’s an assistant with context awareness that can identify and fix its own mistakes. The user simply had to click "Accept" on the corrected command, and the process continued seamlessly.
With the project structure and dependencies in place, Gemini moved on to the core logic.
Importing Styles: It first edited the main index.js file to import the Bootstrap CSS, ensuring the styles would be applied across the entire application.
Creating the Component: Next, Gemini replaced the contents of App.js with the complete React component for the order tracker. This included:
Using React's useState hook to manage the list of orders.
Hardcoding the initial sample data as promised.
Building the JSX to render the data in a clean, responsive table.
Adding a placeholder function to handle status updates.
Finally, Gemini finished by telling us exactly how to see our new app in action: run npm start in the terminal.
We ran the command, and a new browser tab instantly opened, displaying our fully functional "Order Tracker" application. It had a clean title, a structured table with our sample orders, and "Update Status" buttons ready for the next phase of development.
This experiment was about more than just speed. It highlighted a smarter way to work.
Efficiency is King: The most tedious, time-consuming parts of starting a project were automated in seconds. This allows developers to focus their brainpower on building unique features, not on boilerplate setup.
AI as a Collaborator: Gemini didn't just give us code; it gave us a plan, asked for confirmation, and explained its steps. It felt like working with a junior developer—one that types at the speed of light.
Trust Through Transparency: The self-correction feature was the most impressive part. Knowing your AI assistant can catch its own errors builds a tremendous amount of trust and makes you more confident in accepting its suggestions.
For any team looking to accelerate their development lifecycle and boost productivity, tools like Gemini Code Assist are no longer a futuristic concept—they are a practical, powerful, and ready-to-use solution.