Issue Highlights

In this article, I explore how the inherent cognitive limitations of human reasoning affect modelling practices in engineering research.By examining concepts such as emergence, uncertainty, and model usefulness, I argue that engineers must balance realism with practicality, often favouring effective approximations over theoretically "correct" but unusable models.Indeed, in complex systems, claims of realism might be particularly troublesome and misleading.The paper advocates for probabilistic reasoning, epistemic humility, and context-driven model selection as essential tools for advancing engineering knowledge.Theoretical models can still be perfectly useful when they accurately describe experiments, despite potential claims about the real world.