Architecture, performance, and BLE — how we build Flutter apps that hold up on real devices.
When I first started working with navigation in Flutter, I thought the concept was fairly simple: A route takes you from one screen to another. You have a route, you navigate to it, and the corresponding screen opens. But while working on a real navigation flow involving deep links, route
Mobile testing is often seen as verifying layouts across different devices, but this task turned out to involve much more than UI validation. While testing the application, I also worked on implementing UXCam analytics events, which highlighted how closely testing and user behavior tracking are connected. One focused on making
Introduction Background execution on mobile sounds deceptively simple: run this task even when the app isn't open. Anyone who's actually shipped a production app knows how misleading that sentence is. On both iOS and Android, background tasks live under strict OS control. Battery life, thermal limits,
Client applications don't usually fail because of one big bug. They fail because a dozen tiny unbounded behaviors accidentally combine: a user tapping too fast, a scroll listener firing dozens of times per second, a reconnect event triggering a sync job, or a background worker replaying offline writes
A timeline is often the most deceptively complex screen in any modern mobile experience. It looks simple, a neat vertical feed of moments, updates, and events. But behind the scenes it's a battlefield of asynchronous data, inconsistent timestamps, unmerged identities, and late-arriving corrections. In a connected pet-tech ecosystem
Flutter is loved for its smooth animations, reactive UI, and consistent cross-platform behavior. Ask any engineer who's shipped a production-grade Flutter app, though, and they'll quietly admit one painful truth: Flutter apps can suffer from memory leaks, and they're far more common than most
Mobile apps don't live in the same world as web apps. They run on flaky networks, jump between Wi-Fi and 4G, go into the background at random moments, get killed by the OS, and run on devices with wildly different performance profiles. If our backend API is designed
LLM features usually start life in a happy place: a handful of users, low traffic, and plenty of quota. Latency looks fine, tokens are cheap, logs are quiet. Then a product launch, a marketing campaign, or a new "Ask AI" button lands, and suddenly your once-stable service is
Introduction Debugging Flutter apps can feel deceptively complex. The framework promises smooth 60-120 FPS animations and native-like performance, yet in production, hidden issues emerge: rebuild storms, choppy scrolls, network delays freezing the UI, memory spikes, and elusive bugs buried in ViewModels. This guide is a practical, repeatable approach for identifying
Real-time apps are at their best when they feel calm. Numbers update, charts glide, tiles pulse with new information, but nothing spikes, freezes, or drifts. The UI feels more like a live instrument panel than a slideshow. To get there, though, you need more than a WebSocket and a couple