Large language models such as ChatGPT and Claude offer powerful capabilities, but long-form creative work remains a persistent failure point. Projects that begin with clarity and style often degrade into generic, fragmented output. What begins as collaboration turns into cleanup. Two terms now help frame this experience:
Language mummification describes the erosion of voice and vitality in extended LLM outputs. As the model progresses, its prose tends to flatten into list-based exposition and corporate tone. Authentic narrative texture is lost. Narrative labor captures the hidden workload required to make AI-generated writing usable. Users must reassemble fragments, preserve tone, correct drift, and manage prompts beyond what the model can remember. The burden is not eliminated, it is redistributed. These concepts are introduced formally in my new white paper, now available on ResearchGate:
Digital Project Management in the Age of AI: Why Superior Models Need Superior Workflows 🔗 http://dx.doi.org/10.13140/RG.2.2.29888.44805
The paper proposes a system-level response: the Digital Project Manager (DPM), a UX and coordination layer designed to align model capabilities with user goals. DPM offers structure where current tools offer improvisation. This is not just a matter of productivity. It is a question of cognitive fairness and ethical design. Models are improving, but workflows must evolve in parallel.