Aaron Levie

Great read. AI lets you get tremendous leverage that wasn’t available before in almost any domain. That means we’re at a unique moment in history where anyone with a high level of ambition and core skills in any area can overcome a lot of historical experience requirements for their role. This can apply to anyone who’s junior or senior, but it’s pretty sweet that you can do far more than you could have accomplished as a newer employee than even a couple years ago. The people that take advantage of this will get ahead massively. And the companies that find this talent within or outside should put them in key positions to get as much out of them as possible. These people will seem strange and from the future, but they will help you figure out where things are going. Everyone company should be doing whatever they can to find them.

很值得一读。AI 让你在几乎任何领域都获得了此前不存在的巨大 leverage（杠杆效应）。这意味着，我们正处在历史上一个独特的时刻：任何在某个领域具备强烈抱负和核心技能的人，都能突破这个岗位过去对经验的大量要求。这一点对 junior 或 senior 的人都适用；但尤其令人惊喜的是，作为一名较新的员工，你如今能做到的事情，已经远远超过哪怕两年前你本来可能做到的程度。那些善于利用这一点的人，会获得巨大的领先优势。而那些能在公司内部或外部发现这类人才的公司，应该把他们放到关键岗位上，尽可能释放他们的价值。这些人看起来可能有些奇特，像是从未来来的，但他们会帮助你判断事情将走向何方。每一家公司都应该尽其所能找到他们。

The jump from working with a chatbot to having an agent that actually helps automate a process requires a real amount of work. Most companies will need to have dedicated people that are responsible for bringing automation to their teams, instead of leaving this up to every individual employee. Partly because the work is more technical than we imagine today, and partly because it’s just hard to do this as a side project. The job spec is to map out new workflows with agents, implement new systems to deploy agents, make sure the agent has all the right (up to date) context to work with, wiring up internal systems to connect to the agents, creating evals for the agents, figuring out where the human is in the loop, managing the system when there are new upgrades, helping with the change management of the existing business process, and so on. These jobs may come from IT or engineering, or live directly in the business function itself. They’ll be called different things depending on the company, and in some sense it’s the future of software engineering that you’ll see a huge growth of in non-tech companies. Most companies will have to be hiring for this now or in the future, and it’s another example of the kind of new jobs that will be created in AI.

从使用 chatbot（聊天机器人）到拥有一个真正能帮助自动化流程的 agent（智能体），这中间需要投入相当多的实际工作。大多数公司都需要配备专门负责把自动化引入团队的人，而不是把这件事留给每个员工各自去做。部分原因是，这项工作比我们今天想象的更具技术性；另一部分原因是，把它当作一个副业项目来推进本身就很难。这类岗位的职责包括：梳理基于 agent 的新工作流，实施用于部署 agent 的新系统，确保 agent 拥有开展工作所需的一切正确且最新的上下文信息，把内部系统连接到 agent，创建用于评估 agent 的 evals（评测），确定 human in the loop（人类参与环节）应该放在哪里，在系统有新升级时进行管理，帮助现有业务流程的变更管理，等等。这些岗位可能来自 IT 或 engineering（工程）部门，也可能直接设在具体业务职能部门内部。不同公司对它们的叫法会不一样；从某种意义上说，这也是 software engineering（软件工程）的未来形态，你会看到它在非科技公司中出现巨大增长。大多数公司现在或未来都必须为这类岗位招聘，而这也是 AI 将创造的新工作类型的又一个例子。