Tutorial: Build Any App in Minutes with GPTEngineer, no coding required

The future of engineering is being redefined by AI-powered tools like GPT Engineer, which have brought the ability to build complex web applications within the grasp of anyone who can describe what they want in plain language.

After spending a few hours experimenting with the platform, I’m absolutely amazed by its capabilities, especially with the recent integration of SupaBase. This combination allows developers to not only generate frontend interfaces but also seamlessly add a robust backend with database persistence, real-time messaging, and functional calls for edge computing.

The potential is limitless—you can create almost anything you imagine by simply describing it in real-time. In less than an hour, I was able to build a fully functional system including dynamic login, registration, password recovery, and a user dashboard.

This is, without a doubt, the most impressive text-to-app interface I've encountered, marking a transformative leap in how we approach software development.

What is GPTEngineer?

The GPTEngineer.app is a powerful AI-driven tool designed to significantly accelerate the process of building and deploying web applications. It allows users to create full-stack applications using natural language commands, which are then converted into code by the AI. Here's a brief overview of its capabilities and frameworks:

Core Capabilities:

Rapid Prototyping and Deployment: It excels at quickly turning ideas into functional web apps. You can describe what you want to build in plain language, and the AI will generate the necessary code. It supports one-click deployment, allowing for immediate testing and iteration.

Frameworks and Technologies:

• Frontend: It primarily supports frameworks like React, Tailwind, and Daisy UI, but it also allows for simpler setups using HTML and vanilla CSS.
• Backend Integration: Users can connect existing backend services by specifying their API’s OpenAPI specification. This integration ensures that the generated frontend is compatible with your backend, taking it into consideration during the code generation process.
• NPM Packages: It can automatically install NPM packages required for adding advanced features like graphs, maps, or drag-and-drop interfaces.

SupaBase Integration: It can be paired with SupaBase for data storage and retrieval, authentication, and other backend services. Although this feature is still in alpha, it shows promise for handling persistence and user management functionalities.

GitHub Sync: GPTEngineer.app seamlessly integrates with GitHub, allowing you to sync your projects, manage versions, and even transfer projects to your own repositories.

Deployment:

The app offers a one-click deployment feature, making it incredibly easy to take your project live on the web. You can also connect it with GitHub for version control and collaboration, and even customize domains for your deployed projects.

These capabilities make GPTEngineer.app an excellent choice for developers who want to quickly prototype and deploy web applications, especially when integrating with backend services like SupaBase. This should provide a solid foundation for creating a tutorial on using the platform.

How do Get Started

Start by Remixing my Project, I'm calling it "rUv.js"

https://gptengineer.app/projects/3d823dec-c997-46b4-8b0e-53cb75335d20

To kick off your project using GPT Engineer with SupaBase integration, here’s a step-by-step guide based on my experience:

Research and Planning: Before diving in, I used Perplexity to research the requirements for SupaBase, particularly focusing on the data structure and components needed for my project. This helped me draft a comprehensive technical specification, including the initial SQL needed to set up my database schema.

Perplexity Prompt:

create a technical specification using Supabase for login/registration/password reset and user profile management based on the following. I will the GPTengineer UI to created this.

https://docs.gptengineer.app/integrations/supabase/

https://docs.gptengineer.app/features/techstacks/        

Give me the SQL

give me the the entire SQL for supabase including permissions.        

Building the Foundation: With the technical specification in hand, I copied and pasted the SQL and relevant details directly into the GPT Engineer platform. The AI quickly generated the initial code. Although there were a few minor errors, they were straightforward to fix, and within seconds, I had a functional base version of my application.

Next I went to Dribbble and found UI design I liked.

Iterative Development: From there, I incrementally built upon the initial version. Each layer of functionality—whether it was user registration, password recovery, or dashboard features—was added step by step. The platform’s responsiveness made this process surprisingly fast and efficient.

SupaBase Integration: Next, I integrated my SupaBase API key and URL, which allowed the system to persist data, send emails, and handle other registration-related tasks. This integration was straightforward, and the ability to store and update data dynamically added a whole new level of functionality to the application.

Finalizing and Testing: Throughout the process, I encountered a few errors, but these were easily addressed through incremental improvements. By the end, I had a fully functional system that I was satisfied with.

You can explore the link to see each step and the incremental capabilities added along the way. The final product was a result of continuous iteration and quick troubleshooting, showcasing the power and efficiency of GPT Engineer combined with SupaBase.

Let me know what you think!

Try it yourself at: https://ruv-js.gptengineer.run/

Or remix it and great something new at:

https://gptengineer.app/projects/3d823dec-c997-46b4-8b0e-53cb75335d20