In this Saturday office hours session, I do what I always try to do first: open it up for your questions about the Udemy courses you’re taking, what you’re building in your business, or anything you’re stuck on professionally. Then, while we wait for questions to come in, I walk through a real mobile app I’m building in the crypto niche—using Replit AI (what I call “vibe coding”), meaning I’m not hand-coding the app. I’m describing what I want, letting the AI implement it, then testing and debugging like a product owner/engineer. The app idea is simple: show top-moving cryptocurrencies (24 hours / 7 days) and give users context so they can form their own opinion—educational, not financial advice. I demonstrate adding a tappable “coin detail” screen from the trending list, then we hit the real-world problems that matter: API limits, rate limiting, caching, and endpoints that don’t return what you expect. We debug why some coins load and others fail (CoinGecko rate limits), discuss tradeoffs like retries vs. caching, and fix a “new listings” tab that initially showed nothing because it was only pulling the top coins by market cap. The big takeaway: AI makes building dramatically faster than coding from scratch, but you still have to direct it, test it, and make smart decisions around data sources and reliability.