Elvis Omarsar：智能体自动化没有 evals 就是空转代码
这篇推文给正在做智能体自动化的开发者提了个醒：先搭 evals 再谈自动化。对比那些只堆工作流却没度量手段的方案，这个观点决定了项目能不能真的迭代变好。所有在组织里推智能体落地的人都该看看。
Elvis Omarsar 在 X 上发文指出，与多位开发者交流后发现，缺少 evals 的递归自我改进循环只是没有清晰价值的代码行数（LOC）。
他强调无法有效度量就无法有效自动化，任何用于智能体自动化的产品都应将构建和度量 evals 作为一等公民能力，或至少易于支持。他认为这一点不限于软件工程和编码场景，而是适用于组织内所有职能部门。
I've been having several conversations with folks building in both spaces, and it's clear that without evals, that recursive self-improving loop is just more LOC without any clear value. You can't effectively automate what you cannot properly measure. Whatever product you use for agent automation should have a first-class way to measure and build evals explicitly, or support it easily. Pay close attention to this. And this isn't just about software engineering/coding; it's across all functions of the org.
This report is categorized under AITOP's "How-to" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include evals, agents, prompt engineering.
Source attribution: curated from elvis (@omarsar0).
