# Antigravity vs Cursor... The Truth Source: https://www.youtube.com/watch?v=DBsrHm4JwuA Recap page: https://rapidrecap.app/video/DBsrHm4JwuA Generated: 2025-11-21T16:42:12.934+00:00 --- ## Quick Overview The creator successfully integrates Google's new Gemini 3 Pro Image model via CometAPI into a Zapier workflow to automate the creation of custom fashion looks, demonstrating that the agent-driven development environment (Antigravity) handles complex multi-modal tasks involving API calls, database storage (Supabase), and front-end display seamlessly. **Key Points:** - The video demonstrates building an AI Fashion Stylist application using Google's Gemini 3 Pro Image model accessed through CometAPI, integrated via Zapier. - The Zapier workflow successfully triggers image generation using the prompt and selected celebrity data, passes the Base64 image output to Supabase for storage, and displays the results in the custom Lovable app. - Key features of Gemini 3 Pro Image demonstrated include generating realistic images based on multiple inputs (a user photo and up to 10 clothing item URLs) from a single prompt. - The resulting images successfully combine the user's face with various clothing items, such as a colorful shirt, jeans, and socks, in different scenic backgrounds (e.g., European street, park). - The Antigravity AI coding environment is shown planning, coding, debugging (fixing Next.js errors), and managing the entire development pipeline hands-free. - The entire process, from planning the implementation to testing the final application, is completed with minimal manual intervention, showcasing the power of AI-driven development tools. ![Screenshot at 00:05: The video begins by introducing the core task: reviewing new and trending AI tools, specifically focusing on the powerful image generation capabilities of Google's Gemini 3 Pro.](https://ss.rapidrecap.app/screens/DBsrHm4JwuA/00-00-05.png) **Context:** The video showcases the capabilities of Antigravity, an AI-driven development environment, by building a complex web application called 'AI Fashion Stylist'. This application leverages the newly released Google Gemini 3 Pro Image model, accessed via the CometAPI service, to generate personalized fashion looks by combining a user's photo with URLs of clothing items. The entire build process, including Zapier integration for workflow automation and Supabase for database storage of generated images, is managed by the Antigravity agent. ## Detailed Analysis The video details the end-to-end creation of an 'AI Fashion Stylist' application using the Antigravity AI development environment. The initial step involves setting up a Zapier workflow (0:05) to connect CometAPI, which provides access to Google's Gemini 3 Pro Image model. The creator sets a prompt (0:09) to generate 10 unique looks by combining a user photo with up to 10 clothing item URLs. The workflow successfully sends this request to CometAPI (0:38), receives the Base64 encoded image output, and then uses a subsequent step to insert this data, along with the prompt and celebrity name, into a Supabase database table named 'generated_images' (3:34). The application, built using Next.js, successfully fetches and displays these generated images in a gallery interface (5:28), demonstrating the agent's ability to handle multi-modal inputs and database persistence entirely through natural language commands. The agent handles project initialization (7:43), dependency installation, API route creation, frontend styling, and debugging (8:22), confirming that the entire process is highly automated and successful. ### AI Tool Introductions - Reviewing new and trending AI tools, including Google's Gemini 3 Pro Image model (0:02) and the Google Antigravity IDE (6:43). ### Zapier Workflow Setup - Creating a multi-step workflow using a Webhook trigger, CometAPI for Gemini 3 Pro Image generation, and PostgreSQL for data storage (1:38). ### Gemini 3 Pro Image Capabilities - Highlighting features like Base64 output format and the ability to combine up to 14 input images into one output image (0:51). ### Application Demo - Demonstrating the 'AI Fashion Stylist' app, selecting Elon Musk (2:56), Bill Gates (5:51), and Mark Zuckerberg (6:14) as subjects, and generating looks by inputting clothing item URLs (11:15). ### Project Implementation via Antigravity - The agent automatically initializes the Next.js project, sets up environment variables, implements the backend API route, and styles the frontend, ticking off tasks on the implementation plan (7:43, 8:26). ### Final Results and Verification - Successfully generated images incorporating the user's photo with various clothing items appear in the app's gallery (5:44) and are correctly stored in the Supabase database (5:21). ![Screenshot at 0:00: Host introduces the week's new and trending AI tools, setting the stage for demonstrations.](https://ss.rapidrecap.app/screens/DBsrHm4JwuA/00-00-00.png) ![Screenshot at 0:06: Google Antigravity landing page is shown, highlighting the next-generation IDE.](https://ss.rapidrecap.app/screens/DBsrHm4JwuA/00-00-06.png) ![Screenshot at 1:07: Documentation snippet showing Gemini 3 Pro Image supports up to 14 input images combined into 1 output image.](https://ss.rapidrecap.app/screens/DBsrHm4JwuA/00-01-07.png) ![Screenshot at 2:01: The user inputs a complex prompt into the Lovable application builder to create a Midjourney-inspired AI prompt tool, detailing required features like celebrity selectors and Zapier integration.](https://ss.rapidrecap.app/screens/DBsrHm4JwuA/00-02-01.png) ![Screenshot at 5:57: The generated images are displayed, including Bill Gates wearing a rainbow face mask and Jeff Bezos adventuring in the Amazon rainforest.](https://ss.rapidrecap.app/screens/DBsrHm4JwuA/00-05-57.png)