My talk on "New Mathematical Workflows" at Stanford last week is now online: https://www.youtube.com/watch?v=Uc2zt198U_U
One key recommendation in the talk is to now de-prioritize the historical emphasis on competing to be the first to provide a proof for a given unsolved mathematical problem. When we were in the proof scarcity era, the "local" goal of obtaining any proof at all for a problem was fairly well aligned with the more "global" goal of collectively advancing our understanding of mathematics as a community. However, now that the ability to optimize this local goal has increased rapidly to the point of "proof abundance", we have now reached the point where Goodhardt's law https://en.wikipedia.org/wiki/Goodhart%27s_law has kicked in, and further unrestricted overoptimization of this goal will no longer create genuine mathematical progress, and may in fact inhibit it in various ways. However, there is scope for more controlled, and still meaningful, optimization in this direction along carefully chosen workflows (such as mathematics competitions) that are specifically designed to accommodate heavy AI use.