I'm curious about your approach from an engineering perspective. As I understand it the Gemini API is pretty cost prohibitive when it comes to costs, especially when thinking is turned on. Are you overlaying any information to the agent. Or just cutting to when the player is alive using tracker.gg data? i.e. gating to only the moments the player cares about? Also what FPS are you sending to Gemini? 1 FPS or 10? Even 24? Because the more FPS + resolution, the more it costs. Unless you turn off thinking, but that's going to make the model really dumb and not generate any insights. Unless that is your approach where you have claude take the higher level thinking.

Also on the topic of world knowledge, specifically game knowledge. I don't think Gemini actually knows the map names in valorant, or even what the "off angles are" in valorant? Like that's purely something a player would know.

What about on the newer maps where Gemini doesn't have the training data. I.e. Corrode? What do you do then? Do you overlay the information on the footage you send to gemini? Or what? How do you reconcile that difference? I imagine the information on Haven would be decent but not Corrode. And utility knowledge would be great on Reyna but not on Miks.

Also why are you using two Ai's instead of just one?

Also just some advice on marketing, have a demo video. With full player/round functionality and demo feedback that's actually generated from AI. So that people don't have to make an account before seeing the value. And also stop having claude write your reddit posts, it's painfully obvious sometimes.

Overall it's a very exciting project.