2. The constraint is not production

The finding that reframes this discipline, and it is not what most organizations plan for:

The constraint was never how much the agents could produce. It was how much a human could responsibly verify.

Production rises past the verification ceiling; accepted output flattens; the gap is queue

This inverts the usual capacity model. Adding AI capacity does not increase throughput past the verification ceiling — it increases the queue. And a queue of unverified output that looks finished is more dangerous than no output, because it accumulates as apparent progress.

Almost nobody is measuring the verification number. Seats, logins, tokens, completions — all cheap to produce in volume, all nearly free to fake, and none of them the constraint.

The operator's question is not how much can we generate? It is how much can we responsibly accept, and who does the accepting?