As AI systems become more agentic, a central design challenge has emerged: context engineering, the work of assembling the right information, structures, and situational constraints to shape AI behavior effectively. Designing context well determines whether AI applications function effectively, but equally importantly, whether they augment or diminish human agency. This presentation argues that context engineering is fundamentally communication design work, and that technical communication offers disciplinary expertise uniquely suited to it.
You can read more from Dr. Anders at https://abramanders.substack.com/
Three dimensions of our field’s knowledge map onto the core demands of context engineering. Rhetorical and communication analysis provides methods for determining who needs what information, when, and in what form, which comprise the essential analytical work behind any well-designed AI workflow. Genre knowledge captures how communication should be structured for specific purposes, audiences, and institutional contexts, offering transferable patterns for organizing the reference documents, process guidelines, and evaluative criteria that agentic systems require. Human-centered design and user experience design traditions prioritize user agency and participatory approaches, providing frameworks for ensuring that AI-assisted workflows serve the people they are meant to support rather than optimizing around them.
Drawing on recent research mapping worker preferences against AI capabilities, evidence on creativity and productivity impacts in professional contexts, and emerging parallels between AI-assisted coding and writing practices, this talk demonstrates how these foundations translate into practical design competencies for collaborative AI workflows. The presentation illustrates these connections through situated examples—from scaffolded composing workflows that integrate disciplinary methods and frameworks, to innovation processes structured through design thinking—showing how communication expertise can be operationalized at scales ranging from individual tasks to organizational projects. The future-proof path leads not through proficiency with today’s tools but through the design expertise that positions our field as upstream contributors to AI innovation.
Dr. Abram Anders is the Jonathan Wickert Professor of Innovation and Associate Director of the Student Innovation Center at Iowa State University, where he leads the AI Innovation Studio. He created a pioneering Artificial Intelligence and Writing course and conducts research on AI literacies in education. Learn more at abramanders.com.