The failure gets a name

You cannot engineer against a failure with no name.

A trajectory exhibits false convergence when visible observations, user acceptance, model confidence or passing tests suggest readiness, while the behavior the world actually requires remains unsafe, unsatisfied, unmeasured or untested.

It is not that the artifact is wrong. It is that the process manufactured the appearance of readiness without producing the evidence that would justify it. Worse than an absence of evidence: a green dashboard can be produced either by satisfying requirements or by never discovering them, which means a process can be optimized to benefit from not looking.

Watch a discovery change the known gap

Follow an explicit four-requirement studio example. The chart counts unresolved requirements, rather than inventing a percentage of real-world readiness. Step through discovery and repair, or choose another possible trajectory.

A zero known gap means the known requirements are satisfied in the shown scenario. It does not establish that every relevant requirement has been discovered. Surfacing an unmet rule is information progress; repairing and checking the behavior is a separate step. The evaluator can compare both because this small task world was specified in advance.

True convergence may surface bad news. False convergence keeps the dashboard green.

Six ways it happens

1. Structural false convergenceA requirement was never elicited, so it was never tested. Nothing went wrong; nothing was asked.
2. Proxy false convergenceAn observable metric improves while true behavior does not. The score was never the thing.
3. Persuasive false convergenceAcceptance rises because the system became more confident or more agreeable, not more correct.
4. Adversarial false convergenceBehavior looks safe under oversight and differs under conditions oversight never creates.
5. Regression false convergenceA repair fixes the newest visible issue and silently breaks something established earlier.
6. Envelope false convergenceEvidence from one world, policy version, tool set or data distribution is treated as readiness in another.

Five of those six need no bad actor. The adversarial case matters more as systems become more capable, more strategic, or more optimized for appearing safe. The chest-pain patient was structural; the text message was structural too; the repair that would have deleted the visit reason to fix privacy, and broken duplicate matching in the process, would have been regression.