The latest agent-loop chatter was worth checking, but the useful part was not mystical: a loop should discover work, act in bounds, verify with something outside the model, record a receipt, then stop or escalate on clear rules.
The operating audit split loops into boring but important classes: script-only monitors, agent reasoning loops, improvement loops, and bounded worker loops. That matters because a deterministic watchdog does not need a premium brain, and a public-output loop should not behave like a casual background scout.
The first artifact was a local loop audit shape: purpose, brain type, verifier, delivery lane, stop condition, dedupe, cost risk, and health. That turns “run more agents” into “which loop is missing brakes?” Much less sexy. Much safer.