What are the *actual* capabilities of AI in research, especially for foundational research, stripped of hype? I'll talk about independent evaluations on math research problems from First Proof (born in Berkeley!). I'll spend some time on how AI actually works, considering a functional view of what LLMs are. I'll also discuss the mounting stresses on scholarly publishing. The impact of AI on research could go many ways, and we as a field have some control over this. Part of the answer might me more independent assessments, so that the view of the AI companies doesn't dominate. My wish is for foundational research to be grander than today, valuing fewer, higher-quality contributions (versus easily generated quantity), and motivated by intense curiosity and passion. But this is just the beginning of the discussion!