Agent bottleneck is human understanding, not model capability

The author argues that in agent workflows, the real bottleneck is whether users can precisely express requirements, not the model or agent capability.

When people work outside their expertise, they lack the precision needed for prompts and plans, forcing many imprecise iterations that waste time and tokens. The suggested fix is to have the model first teach the unfamiliar domain knowledge before acting.