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 (ACAs) are rapidly becoming embedded in everyday development workflows. Since software engineers (SEs) 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 ACA. Our findings reveal that cognitive engagement consistently declines as tasks progress, and that current ACA designs provide limited affordances for reflection, verification, and meaning-making. Based on these findings, we 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：对人工智能系统的过度依赖会削弱用户的批判性思维，助长自满情绪，而这种风险正因以极少人类干预自主运行的智能体AI系统的兴起而加剧。在软件工程领域，智能编码助手正迅速融入日常开发流程。由于软件工程师所构建的系统部署于多元且高风险的真实世界场景，这些助手不仅应充当自主任务执行者，更需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智能编码助手时的认知投入与意义建构过程。研究结果表明，随着任务推进，认知投入持续下降，且当前智能编码助手的设计在反思、验证与意义构建方面提供的支持十分有限。基于这些发现，我们明确了具体的设计机遇，即利用更丰富的交互模态与认知强制机制来维持投入水平，促进人工智能辅助编程中的深度思考。