这篇论文点出了AI智能体落地的关键瓶颈——软件层，而非模型本身。做智能体开发或架构设计的团队，值得看看DeepSeek的实践如何验证这一观点。
一篇新综述论文提出，自主AI智能体的真正瓶颈不在于语言模型本身，而在于围绕其构建的软件层。工具、内存、测试和权限边界将无状态模型转变为可工作的智能体。DeepSeek已在北京组建专门的“Harness”团队，其核心公式“模型加Harness等于AI智能体”印证了这一论点。该论文强调，代码不仅是AI的产出，更是其思考与行动的方式。
New review paper argues code is how AI agents think and act, not just what they produce
A new review paper argues that the real bottleneck for autonomous AI agents isn't the language model itself but the software layer wrapped around it. Tools, memory, testing, and permission boundaries turn a stateless model into a working agent. Deepseek is already building a dedicated "Harness" team in Beijing with a core formula that confirms the thesis: model plus harness equals AI agent. The article New review paper argues code is how AI agents think and act, not just what they produce appeared first on The Decoder .