The dominant framework treating human-AI interaction as prompt-based instruction execution is inadequate as an account of long-horizon engagement. When interaction extends across repeated exchanges, accumulated history, and developing shared structure, the instruction-execution model fails to capture the phenomena that actually govern behavior. This paper argues that long-horizon human-AI interaction is more accurately understood as a communicative process, subject to the same structural dynamic

