Developer Separates AI Agent Task Execution from Its Own Success Verification

A software developer building a pre-release system called Ranex identified a structural flaw in AI agent pipelines: the same harness that performs a task often decides whether that task succeeded, creating a conflict of interest. To address this, the developer forked the opencode agent harness at a specific commit and locked its plugin surface to prevent unverified components from altering its behaviour. The redesigned architecture separates roles so the harness can only emit work and references, while an independent kernel cross-checks those outputs against its own append-only, hash-chained dispatch record. Completed work is logged as a CANDIDATE rather than a PASS, meaning no approval is granted by the worker that produced it. Final sign-off remains a manual, out-of-band human action to prevent automated self-approval from masking incomplete or incorrect results.