The approval queue is a trust instrument

Any system that proposes changes needs a queue where a person accepts or rejects them. The usual mistake is to think of it as a safety mechanism and nothing else — a gate to get through. It is also, and more valuably, the only honest data you will ever have on whether the automation is working.

The numbers that matter

• Acceptance rate, by category of change. A category below fifty per cent should not be proposed at all.
• Time to decision. Rising time usually means the evidence is getting weaker, not that reviewers are busier.
• Rejections with a stated reason, which are the highest-value feedback the system can receive.
• Changes merged and then reverted — the real error rate, as opposed to the one measured at review.

Those four, tracked over a quarter, answer the question every team asks at the start and cannot answer honestly: how much of this should run without me? The answer is not a philosophy. It is per-category, measured, and it moves.

Design the queue so rejection is cheap

If rejecting requires writing an explanation into a text box nobody reads, reviewers will approve marginal changes to avoid the friction, and the acceptance rate becomes meaningless. Reasons should be a short list of buttons covering the real cases — wrong, not worth it, not now, not your call — with free text optional. You want the rejection to be the path of least resistance when in doubt.

A queue where everything is approved is not evidence of a good system. It is evidence of an unused control.