Workflow-aware alignment becomes a target for human-AI teams

The authors focus on real work settings where humans and AI systems continually hand tasks back and forth. In those environments, alignment depends on timing, role clarity and how the system adapts as the workflow changes.

The framing is useful for enterprise AI teams building assistants into operations. It suggests that evaluation should measure not only answer quality, but whether the model helps the workflow stay coherent and safe.