Field note 009. A replication of a published agent-loop benchmark, and what it hides. Abstract Every agent loop has to decide when to stop. The usual options are a fixed max_iterations or letting the agent declare itself done. In June I published a small benchmark with CDV , an open-source judge for coding agents, showing that a Bayesian adaptive stop rule used 41% fewer steps than a fixed six-step budget while reaching the quality bar on 99.7% of tasks. This note replicates ...