# Building a new feature for my app | coding vlog ep. 3 Source: https://www.youtube.com/watch?v=dcAFUXROlxE Recap page: https://rapidrecap.app/video/dcAFUXROlxE Generated: 2025-11-12T00:01:15.465+00:00 --- ## Quick Overview The founder decided to pivot the initial plan of launching a hiring tool first and instead focused on building the Viral Content Database feature for their app, Yorby AI, to better serve the social media marketing space, even though the initial development phase was longer and more technically complex than anticipated due to needing a robust backend and handling numerous edge cases. **Key Points:** - The founder decided to pivot from building a hiring tool to prioritizing the Viral Content Database feature for Yorby AI, aiming to solve social media marketing problems. - The development of the Viral Content Database feature took approximately one month of deep work, which was longer than the initial two-week estimate. - The core technology enabling this feature is leveraging the Gemini 1.5 Pro API for advanced content analysis and remixing. - The system architecture for content scraping involves an Admin User initiating a workflow via a Next.js Admin App, which triggers an Upstash Workflow to handle verification and scraping logic against various platforms (TikTok, Instagram). - The engineer is currently testing the system with 1-2 videos but plans to test with 100-200 pieces of content next week to ensure scalability and check for errors. - The founder strongly advises other founders to talk to users early, citing that external feedback (even if sometimes contradictory) is crucial for product direction, which is why they are launching a minimal feature first. ![Screenshot at 00:03: The video title overlay 'Startup vlog Episode 3' is displayed over a shot of the founder working on his laptop, setting the context for this development update.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-00-03.png) **Context:** This video is the third episode in a startup vlog series documenting the development of an app called Yorby AI, which aims to be a comprehensive social media marketing tool. The founder is providing an update on the progress made over the past week, specifically focusing on overcoming challenges related to a new content inspiration database feature and the need to incorporate user feedback early in the development cycle. ## Detailed Analysis The founder kicks off the vlog by stating the current date (Thursday, October 16th) and confirming the immediate goal: building out the first major component of Yorby AI, which is the Viral Content Database. This tool is designed to help social media marketers find high-performing viral content for inspiration, allowing them to query content, check if it exists, and then use an AI (Gemini 1.5 Pro) to remix that content for their own needs. The system design, shown via a sequence diagram, involves the Admin User sending video URLs to the Next.js Admin App, which triggers an Upstash Workflow. This workflow verifies admin privileges, then loops through each URL, scraping data (platform, content ID) and checking if the content already exists in the Supabase DB before processing. The entire process is built on a serverless architecture using Vercel and Next.js. The founder admits the initial development took about a month, longer than the two-week estimate, due to complexity, especially around handling edge cases and ensuring resilience against timeouts when scraping large batches of content. A key lesson learned is the importance of getting user feedback early, contrasting with past experiences where too much external input caused distraction. The founder has successfully tested the core scraping logic with one or two videos and plans to test with 100-200 videos next week. The video concludes with a sponsor mention for Warp, an AI-powered terminal, and a brief personal reflection on balancing hard work with taking time off for friends and family. ### Yorby AI Feature Focus - Viral Content Database is prioritized over the hiring tool - The feature allows users to find and remix high-performing viral content - Uses Gemini 1.5 Pro API for content analysis and remixing. ### System Architecture - Admin User initiates content scraping via Next.js Admin App -> Upstash Workflow handles logic -> Verifies admin privileges -> Loops through URLs, scrapes data (platform, content ID) -> Checks Supabase DB for existing content -> Skips scraping if content exists. ### Development Challenges & Learnings - Initial build took one month, longer than the two-week estimate, due to needing a robust backend and handling edge cases like timeouts for large batches (100-200 videos). - Key lesson: Trust your gut and user feedback over external noise. ### Sponsor Integration - The video is sponsored by Warp, an AI-powered terminal that treats coding agents as first-class citizens for development. ### Next Steps - Finalize the client-side UI for the database feature - Conduct larger-scale testing (100-200 videos) to ensure resilience and scalability - Focus on creating a great user onboarding experience. ![Screenshot at 00:04: Title card for the vlog episode displayed over the developer working at a desk with dual monitors.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-00-04.png) ![Screenshot at 00:23: The system sequence diagram detailing the 'Viral Social Media Content Database - System Sequence' flow, showing interactions between Admin User, Next.js Admin App, API Server, Upstash Workflow, Supabase Auth, and Supabase DB.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-00-23.png) ![Screenshot at 00:49: Close-up of the sequence diagram showing the loop logic for processing each video URL, including checking if content exists before scraping.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-00-49.png) ![Screenshot at 03:39: The developer using Warp \(the sponsor\) to manage code changes, showing a successful PR creation via the CLI.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-03-39.png) ![Screenshot at 05:19: A screen showing the Upstash Workflow logs confirming successful execution of a scraping workflow.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-05-19.png) ![Screenshot at 06:14: A detailed view of the sequence diagram showing the backend interaction with Supabase DB to check if content already exists \(content exists? check\).](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-06-14.png) ![Screenshot at 07:35: The expanded sequence diagram showing the final steps: querying content, fetching video, generating script via Gemini 1.5 Pro, and displaying the result to the Content Browser.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-07-35.png) ![Screenshot at 09:29: The developer demonstrating the Warp terminal environment, showing project structure and indexing status.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-09-29.png) ![Screenshot at 10:14: Code review panel in Warp showing the actual code changes made to a TypeScript/React file, with a 'File saved' confirmation.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-10-14.png) ![Screenshot at 15:56: A close-up of the Upstash Workflow success modal showing the execution details \(31 seconds duration, 12 steps\) and the JSON body payload used for the scrape request.](https://ss.rapidrecap.app/screens/dcAFUXROlxE/00-15-56.png)