Reading up on evaluation

Evaluating AI agents requires floor-raising error analysis, code-aware offline tests, production monitoring, and a tight feedback loop rather than benchmark-maxxing.

AI progress follows compute scaling, making evaluation increasingly difficult but promising radical improvements in infrastructure and economic decision-making.