The paper compares different ways to steer model outputs and argues that demonstrations can sometimes provide more practical control than parameter-style settings. That matters for teams trying to make AI systems predictable without adding complex interfaces.
The result is a reminder that user experience and model behavior are closely linked. Better examples, templates and context may outperform more complicated configuration surfaces.