Modern AI agents can analyze large volumes of Perfetto trace data in parallel and uncover potential bottlenecks, but raw traces alone do not provide the framework knowledge needed to explain why an Android UI is slow. This talk presents a framework-aware optimizer that combines deterministic trace analysis with knowledge of Jetpack Compose, Android Views, and Litho to identify issues such as unnecessary recompositions, slow view traversals, and missed component reuse, then connect them to actionable code fixes. Attendees will learn how to combine a shared Perfetto analysis layer with framework-specific plugins and trust gates. Through practical examples, they will see how to turn trace signals into testable hypotheses, map them to source code, verify fixes with before-and-after traces, and recognize when the available evidence is not strong enough to reach a reliable conclusion.