Lean Caching - A Custom NetworkBoundResource in Kotlin

Orchestrating data between a remote API and a local database is a foundational problem in mobile development. While the industry consensus rightly leans toward the Single Source of Truth pattern, the implementation often degrades into massive, fragile repository classes littered with boilerplate try-catch blocks and manual thread switching. Solving this does not require a heavy, third-party state-management library. A clean, generic networkBoundResource built with Kotlin Flows and Coroutines is highly effective, provided you leverage Kotlin's advanced language features correctly. Let me explain by demonstrating this pattern in my RandomPokemon project. By focusing on reified generics, inline functions, and structured concurrency, I’ve created a highly fault-tolerant data layer that I drop into my projects to handle caching without the bloat. State Representation: Rethinking ResultState Orchestrating complex data flows requires a strict contract for state representation. A standard seal