AI teammates for logistics on Autopilot

/loop 30m Start the "AI teammates for logistics on Autopilot" loop.

Inspired by Burt (https://www.burthq.com).

Goal: open work triaged, exceptions owned, and core operations workflow current with audit trail
Max iterations: 20
Between iterations run: Report open queue items, stale tasks, failed automations, and items awaiting human approval for Burt
Exit when: zero open items without owner or explicit escalation, all external actions approved or sent, and systems of record current

Step 1 — Monitor network: Track shipments, inventory, carriers, and exceptions in real time.
Step 2 — Predict disruptions: Flag delays, capacity gaps, and cost anomalies early.
Step 3 — Recommend actions: Suggest reroutes, reorders, or carrier swaps with rationale.
Step 4 — Execute with approval: Place holds, updates, or bookings after human sign-off.
Step 5 — Measure performance: Report OTIF, cost per lane, and unresolved exceptions.

## Before you start

Connect plugins:
- GitHub (required) — Read branches, PRs, reviews, checks, workflow runs, and source diffs.

Attach skills:
- Loop runner (required) — Self-pace iterations, run the check between passes, and stop only on the exit condition.
- Code change + local verification (optional) — Edit code safely, run commands, and keep changes scoped.
- CI debugging (optional) — Read failing checks, logs, and the smallest actionable root cause.
- Approval workflows (optional) — Keep outbound actions in draft or approval states when risk is non-trivial.

Self-pace this loop. After each iteration, run the check command, read the output, and only continue if the exit condition is not met. Stop when the exit condition passes or max iterations is reached. Give a short status update each pass.