Loop Engineering: Version-Bound, Evidence-Gated Coordination for Production Coding Agents

Coding agents can edit repositories and execute tests, yet production software work extends far beyond code generation. It requires durable task context, scoped authority, version-aware approval, source-independent verification, interruption recovery, and accountable handoffs between humans and automated workers. We present Loop Engineering, a method for operating multiple asynchronous agent loops over shared, auditable repository state without relying on private conversational handoffs. Each loop is specified by six elements: a trigger, a context projection, an authority boundary, a verifier, a stop condition, and a write-back rule. Versioned procedural contracts, called Skills, encode reusable operating policy; a Harness bounds the available action surface and collects evidence; human gates authorize high-consequence transitions against exact artifact versions. We report a design-and-experience study from MewDesign, a revenue-generating commercial AI design product. Five specialized loops cover planning, scoped implementation, review, test release, and reconciliation. A cross-sectional audit contains 50 durable marker records across 26 GitHub work items. Five pull requests reached a version-bound test lock: three proceeded to test releases with runtime evidence from sources distinct from the deployment request, and two stopped before merge. A detailed drift episode shows one observed fail-closed path: a new commit invalidated prior approval and evidence, and the workflow refused to reuse stale continuous-integration results. The study is not a controlled benchmark and does not establish causal productivity or general safety. It provides early evidence of feasibility, traceability, and bounded progression in one production setting.