Building Smarter: My Experience with Google AI Studio for Project Development

#deved #learngoogleaistudio #ai #gemini

This post is my submission for DEV Education Track: Build Apps with Google AI Studio.

What I Built

I built an agentic AI application that takes natural language of software projects and automatically generates a complete, production-ready project scaffold.

Here's the prompt that I used;

Design and build an agentic AI application that takes a natural language or voice input describing a software project and automatically generates a base working project directory complete with best-practice folder structure, initial documentation, and required dependencies. The frontend should be built with React (TypeScript) and Tailwind CSS, incorporating text and voice input via the Web Speech API. A Python (FastAPI) backend should process the input using Gemini 2.5 Pro and spaCy to extract project metadata—like app type, features, and tech stack—which is then used by a templating engine (Jinja2) to scaffold the appropriate project directory (e.g., React + Node.js, Django, or Flask). This directory should include a README, architecture docs, .env.example, and requirements.txt or package.json, all auto-generated based on user input. Optional modules should handle dependency installation, code preview, project export, GitHub integration, and one-click deployment to Vercel or Heroku using relevant APIs and shell scripts.

Demo

Here you just need to describe your project.

The bot gets to work scaffolding.

It generates a completely downloadable zip file of the project base.

My Experience

I've used platforms like Lovable and V0 to design front-end frameworks and dashboards, but what sets Google AI Studio apart is its unified ecosystem. Unlike others that require juggling multiple tools and placeholders, Google Studio allows me to create project requirement documents (in PDF), organize resources, build the project, and store everything in one centralized workspace.

That said, there are areas for improvement. I’d love to see version control features that let me easily revert to a previous state if a change doesn’t work out. An autosave function—like the one in other Google apps—would also be incredibly helpful; I once accidentally closed the window and had to start from scratch. Lastly, a built-in GitHub integration for pushing projects directly would make the experience even smoother.

Aside from those suggestions, I had a great experience working through the DEV Education Track and building with Google AI Studio.