Pre-Governance in Production: A Single-Operator Case Study of Constraint-First Governance at the Deployment Decision Surface

Recent work on runtime governance for AI agents has converged on a shared thesis: constraining an agent's decision surface before action is structurally superior to auditing behaviour afterwards. This academic literature is formal, architectural, or testbed-based; it contains no published, longitudinal, single-operator production study. This paper contributes one. From September 2025, a single human operator built and operated nine repositories (eight with production surface area) comprising 802 API endpoints and 319 database models using AI coding agents, governed by a pre-action authorization gate at the deployment decision surface. Check-level instrumentation ran 22 March--24 June 2026 and recorded 2,130 pre-action authorization checks against 44 active constraints, producing 24 constraint activations (22 pre-action, 2 post-action) and zero uses of the formal override mechanism. A separately logged escalation channel (from 15 February — 224 escalations over its wider window, 26 within the check window) shows a natural before/after: in the pre-gate period, approval-first governance saturated (198 escalations in 5 weeks, 60% expiring unadjudicated, 109 of them deploy approvals); after constraint codification, that same push-approval demand shifted to deterministic checks (2,090 of 2,121 auto-allowed), deploy escalations fell to 17, and adjudication demand fell 90% coincident with codification while action volume rose — consistent with the governance-coordination-cost thesis, though causal attribution is not possible at N = 1 where the regime and the operator's behaviour changed together. Two further findings: (i) enforcement strength is a property of interlock placement, not verdict — the deployment gate (a client-side hook, no server-side protection) bound compliant clients only, and a tool-call surface with no interlock detected but did not prevent an agent publishing to an external channel; (ii) the noisiest constraint was tolerated unamended for the full window while amendment machinery was exercised elsewhere, consistent with attention as the binding resource. We state the observability boundary and single-operator limits explicitly, and publish the measurement protocol for replication.