你擅长人工智能，还是只是会使用它？
我们正在制定一个个人AI熟练度的等级体系，希望能得到您对各个等级及其定义的反馈。
<p>L0 新手：对AI完全陌生，或者尚未使用过AI。</p>
<p>L1 聊天：简单的提示与回应使用。工作是串行的：提问，等待回答，然后再提问。</p>
<p>L2 上下文工作：向AI提供相关的文档、数据或工作环境背景，以便它能够在实际的工作对象中进行操作，从而产生更有用的结果。</p>
<p>L3 协同：协调多个代理或AI角色在独立工作流中的合作，工作可能涉及审查、挑战、比较或基于其他工作的基础进行构建。这不仅仅适用于工程领域。</p>
<p>L4 自动化：创建由业务事件触发的工作流程，并在没有人坐在电脑前逐步指挥的情况下运行。</p>
<p>L5 循环：将这些工作流程的输出反馈到共享知识或公司智库中，以便未来的工作流程随着时间的推移不断改进。</p>
我希望能听到您对以下几个问题的看法：
<p>这些等级是否合适？</p>
<p>有没有名称不清晰或重叠的情况？</p>
<p>您会用什么可观察的行为来区分不同的等级？</p>
<p>“循环”作为一个个人熟练度等级是否合理，还是它本质上是一个团队或公司能力？</p>
<p>是否存在L6，如果存在，您会如何定义它？</p>
我们之所以想要定义这些等级，是因为在与客户的对话中，我们发现人们在自我评估自己的AI熟练度时并不太擅长。频繁使用往往被误认为是熟练度。而在这样的等级体系中处于较低水平可能会让人感觉像是在承认自己落后、不合群，或者在工作中缺乏安全感，尤其是对于那些被期望引领节奏的领导者。我们希望找到一种更客观、基于行为的方式来区分这两者。
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We’re working on a ladder for individual AI proficiency and would love feedback on both the levels and the definitions.<p>L0 New: brand new to AI, or has not yet used it.<p>L1 Chat: simple prompt-and-response use. Work is serial: ask, wait for an answer, then ask again.<p>L2 Contextual Work: gives AI relevant documents, data, or workspace context so it can work within the actual artifact and produce a more useful result.<p>L3 Orchestrate: coordinates multiple agents or AI roles across independent workstreams, with work that may review, challenge, compare, or build on other work. This is not just for engineering.<p>L4 Automate: creates workflows that are triggered by business events and run without someone sitting at a laptop directing each step.<p>L5 Loop: feeds the output of those workflows back into shared knowledge or a company brain, so future workflows improve over time.<p>A few things I’d love your perspective on:<p>Are these the right levels?
Are any of the names unclear or overlapping?
What observable behaviors would you use to distinguish one level from the next?
Does “loop” make sense as an individual proficiency level, or is it inherently a team or company capability?
Is there a L6 and if so how would you define it?
We’re trying to define these because, in customer conversations, we’ve found that people are not very good at self-evaluating their own AI proficiency. Frequent use often gets mistaken for proficiency. And being low on a ladder like this can feel like admitting you are falling behind, do not fit in, or are less secure in your job, especially for leaders expected to set the pace. We want a more objective, behavior-based way to distinguish the two.