This position paper's characterization of expository writing as evidence-based and knowledge-generating has shaped how subsequent work frames challenges in AI-assisted writing — it is cited to motivate research on knowledge-intensive text generation, to justify the importance of sensemaking and outline planning beyond simple summarization, and to ground the design of multi-document synthesis tasks such as literature reviews and Wikipedia article writing. Its proposed three-stage pipeline (evidence extraction, synthesis, and composition) has been directly adopted as an architectural blueprint for LLM-based expository writing systems, while its broader vision of human-AI collaboration for complex writing has spurred work on knowledge synthesis tools, role-play-based information gathering approaches, and AI writing assistants that enhance rather than replace author thinking. Additionally, its framing of expository writing tasks has been used to define new NLP benchmark tasks and to contextualize user information-seeking behaviors during writing.