Public AI benchmark or personal replay set?

A practical question about when public AI benchmarks should lead tool choice and when personal replay tasks should decide adoption.

Public AI benchmarks are useful for discovering which tools deserve attention, but I do not think they should decide daily adoption by themselves. For coding agents and workflow tools, a small personal replay set seems more predictive: one repo edit, one messy handoff, one source check, one multilingual tone task, one debugging case. Those show whether the tool fits the actual work. What would you put in a replay set before switching daily AI tools?