Naa College Blog / AI Tools and Vibe Coding
How to Build Your First Website with Google AI Studio
A practical beginner workflow for building a web prototype in Google AI Studio, reviewing generated code, testing behavior, and preparing a safer deployment.
Updated 2026-10-11 · By Naa College
Google AI Studio is a browser-based environment for trying Gemini models and building applications. Its Build mode can create and iterate on web apps from natural-language instructions; the available workflow and capabilities can change, so use the current official documentation alongside this guide. A generated prototype is a starting point—not proof that an app is secure, correct, or ready for real users.
1. Start with a small, clear brief Before opening Build mode, write down: - Who will use the app? Describe the intended audience. - What task should it solve? Keep the first version focused on one main workflow. - What screens are needed? List only the essential pages and states. - What data is involved? Identify whether it uses sample data, user-entered data, a database, or an external API. - What must not happen? State constraints such as no paid services, no authentication, or no unrelated redesign.
For example: “Build a responsive study planner where a student can add tasks, mark them complete, and filter by status. Use sample data only. Include empty states and keyboard-accessible controls. Do not add accounts, external APIs, or paid services.”
2. Use Build mode in stages 1. Open Google AI Studio and select Build mode. 2. Describe the smallest useful version of the app. 3. Review the preview and test the main flow before adding more features. 4. Ask for one focused change at a time, such as form validation or mobile layout. 5. Use the Code view to inspect the files and understand how the project is organized. 6. If importing a repository, ask for an audit first and explicitly protect existing routes and functionality.
The current official Build mode documentation describes supported workflows, including creating apps through prompts and continuing development outside the initial preview.
3. Test beyond the happy path Check empty fields, invalid inputs, long text, narrow screens, keyboard navigation, loading states, failed requests, and missing pages. If the project uses APIs or a backend, inspect where requests happen and how errors are handled. A screenshot only proves that one screen rendered; it does not prove every interaction works.
4. Review code and protect credentials Read the generated code before publishing. Check dependencies, permissions, form behavior, accessibility, and whether the app sends information to external services. Never put private keys, service-account credentials, passwords, or other secrets in frontend code: browser-delivered JavaScript can be inspected. If a service requires a secret, use an appropriate server-side design and secret-management approach rather than embedding it in the client.
5. Understand deployment and cost Confirm the target hosting platform, environment variables, domains, privacy disclosures, and any external service limits. API usage or deployment may have limits or costs depending on the selected product and plan. Verify current terms and billing details instead of assuming everything is free.
6. Before sharing the app - Test the production build and the deployed URL. - Check links, page refreshes, mobile behavior, and browser-console errors. - Keep a Git checkpoint and a way to revert a broken release. - Explain known limitations to users.
Key takeaway: AI Studio can speed up the first implementation, but you remain responsible for checking the code, privacy, reliability, and maintenance.
Official and reference sources
Educational information only. Verify time-sensitive details with the relevant official authority or product documentation.