The expensive mistake in incident response is confusing what you have observed with the boundary of what happened.
That is why this line matters.
Most organisations still evaluate AI as an answer machine: retrieve the evidence, summarise the findings, draft the report.
Useful—but bounded by the questions humans already thought to ask.
The more consequential capability is hypothesis generation: identifying the next uncertainty worth investigating.
That does not prove there are other victims. It does not establish a broader compromise. It gives investigators a testable question that may otherwise have arrived too late—or not at all.
The cost of missing that question is not a weaker summary. It is false containment: closing the incident while part of the problem remains undiscovered.
In high-stakes work, intelligence is not merely producing better answers. It is refusing to mistake the visible incident for the whole problem.
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