<p>Generative AI is embedded in everyday knowledge work, but we know little about how workers preserve human agency when large language models (LLM) output enters real deliverables. Drawing on 15 interviews in two early-adopting German tech firms and analysis of handbooks and workflow artifacts, we examine how professionals keep control and responsibility when LLM generate parts of their work. We focus on three phases where people step in: drafting with the AI, refining its output, and reviewing the final product with others. We derive a nine-step checklist that specifies what practices to apply, and when, to keep AI-assisted text reliable, traceable, and accountable. We contribute by (1) explaining how ownership and discretion jointly ground human agency in GenAI workflows, (2) mapping when and how judgment shifts between humans and LLMs across drafting, refining, and reviewing, and (3) deriving a nine-step Oversight Protocol (OP-9) that embeds simple checks at key points in the workflow.</p>