As generative AI tools become embedded in technical communication classrooms, educators often respond by adapting assignments to new tools or debating policies of adoption and restriction. While these responses are necessary, they can unintentionally prioritize short-term tool management over sustainable pedagogical design. This presentation argues for a future-proof approach to AI pedagogy by reframing generative AI not as a collaborator or replacement for student labor, but as an algorithmic mirror that reflects—and intensifies—our existing pedagogical assumptions about context, agency, and rhetorical judgment. 

Drawing on sustained, reflective engagement with a large language model across teaching, research, and writing tasks, this presentation synthesizes insights from recent technical communication scholarship with lived pedagogical practice. Rather than focusing on tool-specific instruction, it examines three durable pedagogical lessons that emerge when GenAI is treated as a socio-technical rhetorical system rather than a neutral assistant.