Introduction Building a mobile application that handles sensitive financial data — crypto transactions, KYC verification, gift cards — means security is not an afterthought. It is a core deliverable. During the development of a cross-platform fintech application, one of the non-negotiables on the security checklist was runtime application self-protection (RASP). After evaluating our options, we
React Native's New Architecture — JSI, Fabric, and TurboModules — has been "coming soon" for long enough that some teams wrote it off as vaporware. It shipped. It is now default in new React Native projects. And it meaningfully changes how the framework works at the performance-critical boundaries between JavaScript and native code. This post is not a getting-started guide. It is an honest account
Originally published on rohitraj.tech UPI fraud hit ₹805 cr in India last year. Cloud APIs leak data. So I built ScamRakshak — fully on-device scam detection. 3-tier inference engine: Gemma 4 LLM — context-aware classification LiteRT — fast pattern model Regex fallback — when battery low Full architecture write-up: https://rohitraj.tech/en/notes/build-on-device-ai-scam-detector-android-gemma Read
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
I have been building web apps for 12 years. In that time I never wrote a single line of mobile code. Not Swift, not Kotlin, not even a basic React Native hello world. That changed last month because of my wife. She has been using Synapse, the AI companion I built for her, every day from her phone browser. If you are new here, Synapse is a personal AI that uses a temporal knowledge graph instead of
🚀 I Served My React SPA from Android Assets Like a Professional Web Server — Here's What Happened First load: 77ms. Reload: 2ms. 38x faster with LRU cache. No server, no permissions, no dependencies. 🤔 The Problem Every React Dev Faces You've got your SPA running perfectly on localhost:5173. React, TypeScript, TailwindCSS, React Router, lazy loading... everything works beautifully. Now you need
Hello Developers! 👋 Most developers today pick a side: Let’s talk about combining C++ and JavaScript—the ultimate hybrid stack for high-performance applications. 👇 1. The Core Engine (C++) ⚙️ 2. The Browser Bridge (WebAssembly) 🌉 3. The Cinematic Experience (Vanilla JS + UI/UX) ✨ The Takeaway 🎯 Keep optimizing, keep building! 💻✨ ~ Ujjwal Sharma | @stackbyujjwal About the Author 👨💻 Ujjwal
I built a Vamana-based vector search engine in C++ called sembed-engine. Recently I made a pull request that sped up queries by 16x and builds by 9x. The algorithm stayed exactly the same. The recall stayed at 1.0. The number of visited nodes did not change. The speedup came from data layout. The original code stored vectors as separate objects pointed to by shared_ptr: struct Record { int64_t