Over-reliance on AI systems can undermine users' critical thinking and promote complacency, a risk intensified by the emergence of agentic AI systems that operate with minimal human involvement. In software engineering, agentic coding assistants are rapidly becoming embedded in everyday development workflows. Since software engineers create systems deployed across diverse and high-stakes real-world contexts, these assistants must function not merely as autonomous task performers but as Tools for Thought that actively support human reasoning and sensemaking. We conducted a formative study examining software engineers' cognitive engagement and sensemaking processes when working with an agentic coding assistant. Our findings reveal that cognitive engagement consistently declines as tasks progress, and that current agentic coding assistants' designs provide limited affordances for reflection, verification, and meaning-making. Based on these findings, e identify concrete design opportunities leveraging richer interaction modalities and cognitive-forcing mechanisms to sustain engagement and promote deeper thinking in AI-assisted programming.

翻译：过度依赖人工智能系统可能削弱用户的批判性思维并助长自满情绪，而自主人工智能系统的出现——其运作几乎无需人工干预——加剧了这一风险。在软件工程领域，自主编码助手正迅速融入日常开发工作流程。鉴于软件工程师构建的系统将部署于多样化且高风险的真实场景，这些助手必须不仅作为自主任务执行者，更应成为积极支持人类推理与意义建构的"思维工具"。我们开展了一项形成性研究，考察软件工程师在使用自主编码助手时的认知参与及意义建构过程。研究发现：认知参与度随任务推进持续下降，且当前自主编码助手的设计在支持反思、验证与意义生成方面存在明显局限。基于这些发现，我们提出了具体的设计改进方向，通过利用更丰富的交互模式与认知强制机制来维持参与度，促进人工智能辅助编程中的深度思考。