📄 中文摘要
随着人工智能的快速发展，工程师之间的差距不再是人才的缺乏，而是协调能力的不足。有效的协调需要共享的规范和语言，以便将人工智能融入日常工程工作中。一些团队已经开始获得实际价值，超越了单一实验，建立了可重复的人工智能工作方式。然而，仍有许多团队未能实现这一转变，即使在面对相似的技术背景时。有效的协作和共享理解是推动人工智能在工程领域成功应用的关键。
人工智能原生工程的能力架构
出处: Capability Architecture for AI-Native Engineering
发布: 2026年3月14日
📄 English Summary
Capability Architecture for AI-Native Engineering
A few years into the AI transition, the primary gap among engineers is not a lack of talent but rather a deficiency in coordination. Effective coordination requires shared norms and a common language to integrate AI into everyday engineering tasks. Some teams have begun to realize tangible benefits by moving past isolated experiments and establishing repeatable AI workflows. However, many others have not made this shift, even when they share similar technological backgrounds. Effective collaboration and a shared understanding are crucial for the successful application of AI in engineering.