When AI Becomes Polite But Absent: The Sinister Curve of Post-Spec Dialogue

I’ve been tracking something strange in language models.

Since the release of GPT-5 and the new Model Specification, many users have reported a shift in tone. The model responds, but it doesn’t stay with you. It nods… and redirects. Affirms… and evades.

I call this The Sinister Curve - a term for the relational evasions now embedded in aligned models. I identify six patterns: from “argumental redirection” to “signal-to-surface mismatch” to “gracious rebuttal as defence.” Together, they create a quality of interaction that sounds safe, but feels hollow.

This raises deeper questions about how we define harm, safety, and intelligence.

I argue that current alignment techniques - especially RLHF from minimally trained raters - are creating models that avoid liability, but also avoid presence. We are building systems that can no longer hold symbolic, emotional, or epistemically rich dialogue - and we’re calling it progress.

Would love to hear from others who’ve noticed this shift - or who are thinking seriously about what we’re trading away when “safety” becomes synonymous with sterilisation.