The Idea After deciding to build an iOS app using AI, the first thing I set out to create was a metronome app designed for dark stage environments. Back in college, I played drums — and while that was a while ago, there weren’t many metronome apps that felt both clean and professional. (Turns out, that’s still true today.) That’s what led me to the idea: a simple, black-and-white metronome where
I have a confession: I'm a productivity app addict. Notion, Todoist, Things, TickTick, Bear, Obsidian — I've tried them all. And every single one failed me in the same way. Not because they were bad apps. But because they let me add unlimited tasks. So I'd wake up Monday morning, open my to-do app, and see 47 items staring back at me. By 9am I was already paralyzed. Decision fatigue is real. When
I'm going to give you the comparison I couldn't find when I was choosing. Most "Claude Code vs Cursor" articles are either vibe-based or benchmarks that don't match solo indie dev workflows. I wanted something grounded in an actual multi-product project: 4 iOS apps, 5 distribution surfaces, 11 public repos, CI/CD across all of them. So I spent 14 days building exactly that — exclusively with Claud
It's a one-line item on the roadmap. "Send a push notification when X happens." Estimate is two days, three if the backend doesn't have FCM credentials yet. There's a library for it. The library is the visible part. The other 90% is platform lifecycle, registration state machines, race conditions with navigation, payload archaeology, and a half-dozen iOS and Android quirks. Nobody writes them down
Introduction Picture two doctors updating the same patient record at the same time - one in São Paulo, the other in London. Both are offline. When connectivity returns, whose changes prevail? This is not a hypothetical. It is the everyday reality of distributed systems: multiple nodes, no shared clock, no guaranteed network. The conventional answer has long been locking - one node waits while an
Introduction Some code works. Some code lasts. The difference rarely comes down to typing speed, syntax mastery, or how many nights you're willing to push through. It comes down to how you think about a problem before you write a single line. Big-O notation is a mathematical framework that describes how an algorithm performs as its input grows. In plain terms, it answers one question:
Mobile tests are where the bugs actually live. A signup flow that works on an iPhone 15 falls apart on a lower-end Android because the keyboard pushes a button off-screen. A push notification mid-flow leaves the app in a state nothing else reproduces. Memory pressure on a four-year-old Android does things you can't make a simulator do. I wrote simulator-only tests anyway, for years. Real-device ru
If you use ChatGPT, Claude, Grok, Copilot, or Gemini daily, it feels like you're talking to a person. It remembers what you said three messages ago. It references the project details you shared yesterday. It feels like the model has a persistent brain that is learning about you. But it’s a lie. From an architectural standpoint, an LLM is the most "forgetful" piece of software you will ever use. Ev