Hey Slabak, I’ve been thinking about how we could use pattern recognition from human gameplay to tweak our team’s moves—sort of a predictive model that learns from past errors. Do you see that as a useful edge, or are we just chasing noise?

Sounds solid—just remember to keep the model lean, use validation sets, and stop when the fit starts mirroring the noise. If there’s a rhythm, we’ll capture it, otherwise we’re just chatting with ourselves. Let’s keep an eye on the data and not let our ego get in the way of good strategy.