Most conversations frame it as tool accuracy, but in practice, outcomes seem far more dependent on workflow discipline than the detector itself. Clean human writing gets flagged. Lightly edited AI slips through. Same detector, different day, different result.
So I’m curious:
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Are people actually testing detectors with controlled inputs, or just reacting to one-off flags?
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What false-positive rate are you seeing on genuinely human-written content?
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At what point in your workflow do detection issues usually appear — draft stage, post-edit, or final publish?
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Has anyone seen a detector that’s consistently reliable across hybrid content, not just raw AI?
Feels like we’re treating detection as a binary verdict when it’s really a signal quality problem. Interested to hear what’s holding up outside of demos.