From "You Have a Bug" to "Here's the Root Cause" - Adding AI Code Analysis to My App Review Pipeline

TL;DR: I built an app review pipeline that classifies bugs and crashes. It was useful but stopped at "what's wrong." I extended it to answer "where in the code" and "what to change" — using a PydanticAI agent with codebase exploration tools, then made the analysis engine pluggable so it can use Grok Build, Claude Code, or OpenAI Codex as backends. Here's how I got there, what broke along the way, and how the architecture ended up.

Where I Started

I have a CLI tool called AppPulse that monitors my app's reviews and crash data. Every morning it:

Pulls new reviews from Google Play / App Store

Classifies each one with an LLM — bug, crash, feature request, performance, praise