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Design Note — Post-Release Operating Model (community loop + simulate-before-implement)

Status: Standing direction from the operator, shaping Stage 5+ design. Date: 2026-06-11.

The vision

Once Loomwave is released and fielded:

  1. GitHub is the community surface. Feature requests, bugs, enhancements, and field reports arrive as issues; an AI maintainer semi-automatically parses, triages, and acts on them — triage → reproduce/evaluate → propose → human approval. Not fully autonomous; the human gate stays.
  2. Simulate-before-implement is a standing gate. Fielded nodes feed back enough operational telemetry that any proposed change can be evaluated in simulation against real measured conditions — effectiveness, performance, impact — before a line of firmware changes.

This generalizes the discipline that built the project: every Stage-2 decision was sim-backed; every Stage-4 milestone was hardware-measured; v8 calibrated the sim against live networks. The vision makes that loop continuous and community-fed rather than a one-time development practice.

What it requires of the system (design rules, effective now)

  1. The simulator is a permanent first-class artifact. Every protocol change MUST land in the SimPy model in the same change-set as spec/firmware (sim–spec–firmware versioned together). Model drift silently breaks the evaluate-before-implement loop. The existing pattern — real-topology seeding + calibrated propagation (v8) — is the prototype: simulation scenarios are generated from operational telemetry, not hand-authored.
  2. Telemetry is designed-in, not bolted on. INFRA daemons emit structured operational logs (the drive-test CSV is the seed): slot utilization, delivery ratios, per-link SNR distributions, churn/fallback episodes, replay rejects, desense events. A versioned telemetry schema + export bundle gives field reports a machine-readable attachment format.
  3. Privacy hooks in the export path. Positions and identities are sensitive; the export tool anonymizes by default (same sensibility as operator-access-options.md).
  4. GitHub plumbing at release time: issue templates (bug / feature / field report with telemetry bundle); CI that runs the sim regression suite on every PR and posts the scenario numbers (delivery/latency/util deltas) as the PR's evidence; labels/automation the AI maintainer drives.

Refinement: UI is a different change class

Protocol changes make falsifiable claims — a sim gate fits. UI/UX changes (Android app, client device screens) are preference-driven: there is no objective function to simulate, and one design cannot satisfy the opinion space. Strategy direction (open, under consideration): make the UI easily customizable by end users rather than evidence-gating a single design. A spectrum of mechanisms exists — theming/layout preferences → user-selectable mode profiles (e.g. drive-test / emergency / casual messaging) → declarative or community-variant UIs users opt into.

The architectural enabler is already mandated (CLAUDE.md Stages 6–7): protocol/business logic behind a stable protobuf API with MVVM/clean separation — the UI must remain a thin, swappable layer for any of those mechanisms to work. Any UI usage telemetry would be opt-in and privacy-reviewed, unlike node operational telemetry.

What this changes immediately