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Presents a verification instrument for long-horizon agents that structurally separates commitment drift from binding drift, using a deterministic executive and pre-registered predictions. Reports ablation results showing commitment mechanism removal flips goal abandonment from 0 to 1 while binding error stays flat, though task efficacy is null on ARC-AGI-3.
Discusses the difficulty of verifying outputs from autonomous agents after long-running tasks and asks about using critic agents or traceability tools to ensure trustworthiness.
The article describes lessons learned from building a 'harness' system to wrap coding agents with context, tools, provenance, and verification, detailing the first two of eight pillars: Context and Provenance.