Identifying bottlenecks is pretty generalizable. There is a distinction the skill tries to draw between targeting median FPS and P95, but from there the AI is quite good at narrowing to the relevant data.
Where the AI trips up is getting distracted by aggregate signals instead of digging deep into root causing specific frame drops, but I see humans and existing tooling getting distracted by that too.
Root causes are often context-dependent, but they tend to cluster into a handful of common issues. If you're able to enable the new swiftui instrument (from WWDC 2025), the entire attribute graph is encoded, and it can get you to the precise issue quite well.
Where the AI trips up is getting distracted by aggregate signals instead of digging deep into root causing specific frame drops, but I see humans and existing tooling getting distracted by that too.
Root causes are often context-dependent, but they tend to cluster into a handful of common issues. If you're able to enable the new swiftui instrument (from WWDC 2025), the entire attribute graph is encoded, and it can get you to the precise issue quite well.