Finding a memory leak is only the beginning. The difficult part is understanding why it happened, navigating from a heap trace back to source code, and deciding how to fix it. In this session, I'll take you inside LeakLens, an open-source Android Studio/IntelliJ Platform plugin I built to create an end-to-end memory debugging workflow directly inside the IDE. We'll follow the complete journey from an Android device to an actionable fix: discovering a debuggable process, capturing and transferring a heap dump through ADB, analyzing it with Shark, deobfuscating reference traces, and connecting leak information back to source code through IntelliJ PSI. We'll then go beyond standard heap analysis and explore how LeakLens extends Shark with domain-specific inspectors for modern Android patterns including Jetpack Compose, coroutines, WorkManager, ViewModels and navigation, while UAST-based inspections provide complementary static analysis across Kotlin and Java. The session will also cover the less visible engineering challenges of building IDE tooling: handling unreliable process discovery with ADB/JDWP fallbacks, running expensive heap analysis without blocking the IDE, managing large HPROF files, navigating across Android Studio API differences, and regression-testing heap analysis using golden files. Finally, we'll look at privacy-aware AI-assisted contextual remediation and how these pieces come together to create a detect, analyze, understand, fix workflow for Android memory problems. The goal isn't to build another wrapper around LeakCanary or Shark. It's to explore how low-level Android debugging data can be transformed into an integrated developer workflow that reduces the distance between "there is a leak" and "here is where I should fix it."