A first-person engineering account from 掘金 · 人工智能 describes a two-month redesign of an LLM Agent Plan system from a dependency-based DAG to a linear checklist. The author attributes the change to verification failures that rolled steps back, inaccurate dependency declarations, difficulty tracking substantive work, and a mismatch between fixed benchmark tasks and dynamically evolving production work. The report concludes that the engine should provide signals while leaving completion judgments to the model, while noting that DAGs may still suit multi-agent or batch workflows with clear dependencies.