Automating Android Root Cause Discovery with AI: Crashlytics, MCP, and Claude 4.8 Every Android app that ships crashes. Users hit unexpected states, device configurations trigger edge cases, and third-party libraries fail in mysterious ways. The traditional approach to bug fixing is manual: you read the stack trace, search for the failing line, mentally reconstruct the […]
The Problem With How Most Developers Use AI Today You open Claude Code or Cursor, describe what you want, and the agent immediately starts generating code. Sounds great, right? Except ten minutes later, you’re staring at a ViewModel that ignores your DI setup, tests that weren’t written, and a pattern that doesn’t match anything else
The Stack Trace Triage Problem Every app that ships crashes. Users hit unexpected states, device configurations trigger edge cases, third-party libraries fail in mysterious ways. When a crash report lands in Firebase Crashlytics, you’re looking at a stack trace, maybe some breadcrumbs or custom logs, and you need to decide: Is this a high-priority bug?
Rubber Duck Debugging with AI: The Modern Approach “Rubber duck debugging” is an old technique: you explain your bug to an inanimate object (a rubber duck), and in the process of explaining, you discover the problem yourself. Today’s AI assistants make this technique more powerful. Instead of talking to a duck, you can ask an
