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Sample article: the scenario, people and numbers are illustrative.

Explainer · Software delivery

Faster agents do not shorten a review queue

If changes arrive faster than your reviewers clear them, the queue grows no matter how fast the agent wrote them. Changing who reviews what shortens it.

17.4 → 11.9 s
Same 12 demo changes, two review processes. Demonstration data.

Twelve demo changes go through two review processes with the same arrival times. Lane B writes code at the same speed as lane A and finishes 5.5 s sooner, because it sends each finished change somewhere else.

Finding: the same twelve changes finish 5.5 s apart

Both lanes receive every change at the same moment. Lane A sends each one to a single reviewer. Lane B sends routine changes to automated checks and only the rest to the reviewer.

Figure 1

Same changes, two review processes

Demonstration data. Concept, not measurement.

  1. 01 · Same changes, two lanes

    Demo: twelve changes become ready for review, one every 0.9 s. Both lanes receive every change at the same moment.

  2. 02 · Lane A's line grows

    One reviewer needs 1.4 s per change while a new one arrives every 0.9 s, so lane A's line grows. Lane B sends routine changes to 0.35 s checks and never builds a line.

  3. 03 · Arrivals stop

    The last change arrives at 10.5 s. From here both lines can only shrink: that is the end of the inflow, not the policy. Lane B finishes at 11.9 s.

  4. 04 · Lane A drains last

    Lane A is done at 17.4 s. Same changes, same arrival times: the 5.5 s difference comes from the review process.

What happens in lane A?

Mechanism: one reviewer, a new change every 0.9 s

A reviewer decides whether a change is safe to ship. In lane A that reviewer needs 1.4 s for each change, and a new change arrives every 0.9 s, so the line grows for as long as changes keep arriving. A faster agent makes them arrive sooner and changes nothing else.

If your team opens more pull requests each week and merges the same number, you are looking at lane A over days instead of seconds.

What changes when the arrivals stop?

Evidence: the gap comes from the process

The last change arrives at 10.5 s. From then on both lines can only shrink, with or without a policy, because nothing new comes in. Do not credit that drop to any process; the figure gives it a step of its own.

Lane B finishes at 11.9 s and lane A at 17.4 s. Inflow is identical in both lanes, so the review process accounts for the whole 5.5 s.

How do you find lane B on your team?

What to do: split the review wait by change type

Your code host already records three timestamps for every change. The gap between the last two is the wait.

Timestamp What it marks
Opened The author created the change
Review requested The change joined the queue
Merged A reviewer or a policy let it through

Split the wait by change type before you change anything. If one or two types make up most of it and a policy can decide them, you have found lane B. If every change needs judgement, add reviewers.

Questions

Anything a policy can decide without judgement, for example a dependency update inside a pinned range or a copy edit outside regulated text.
The owner of the policy that let it through. Name that person before you turn the policy on.

Updated . Drafted with AI assistance; reported, checked and edited by Sample Author.

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