Reading up on Mercor

AI progress is constrained by long-task reliability, labor reallocation, cost inefficiencies of general APIs, the declining value of raw coding skills, inadequate benchmark testing, the limits of formal verification without strong specs, memory-bound local hardware advantages, the shift from data to environment-driven training, and the rising competitiveness of US open-weight models.

Tens of thousands of professionals are joining Mercor to train AI by performing tasks that mirror their own jobs, effectively teaching the technology to replace them.