Great post on FDEs. Everyone should read it if you’re interested in this job category. This is a job that is going to be around as long as AI keeps changing rapidly, which it inevitably will. People often wonder why isn’t this like just deploying other forms of technology in the past, like cloud. Because something like cloud adoption affected a fairly concentrated set of users (developers and IT), and generally didn’t require a fundamental change to the workflows of employees to get the benefits of the new service being delivered on the cloud. At best you went to one training session and you were done. With agents, the work to implement them is not only highly technical, but they directly impact the underlying workflows that people participate in. This means there’s a ton of technical work and change management that comes with it. Further, the pace of change of cloud wasn’t nearly as quick, so there was a lot more time for best practices to propagate. Now, every model change means either something new can be done that wasn’t possible before, or some piece of scaffolding is now redundant or holding you back. This is why it’s commonly easier for a vendor or partner that’s seen the implementation hundreds or thousands of times help do the work, even with internal support from the customer. So, this job isn’t going away any time soon, and will be a great path for a lot of technical talent, especially early career.
关于 FDEs 的这篇帖子很棒。如果你对这一类岗位感兴趣，人人都应该读一读。只要 AI 继续快速变化——而它几乎必然会如此——这类工作就会一直存在。人们常常会问，为什么这不像过去部署其他技术形式，比如 cloud（云）？因为像 cloud adoption（云采用）这样的事情，影响的是一组相对集中的用户（developers 和 IT），而且通常并不需要从根本上改变员工的工作流程，就能获得把新服务部署到云上的收益。很多时候，你最多参加一次培训就结束了。但对于 agents（智能体）来说，实施它们的工作不仅技术性很强，而且它们会直接影响人们参与其中的底层工作流程。这意味着随之而来的不仅有大量技术工作，还有变更管理。此外，cloud 的变化速度根本没有这么快，所以最佳实践有更多时间传播。现在，每一次 model（模型）变化都意味着：要么出现了以前做不到的新能力，要么某些 scaffolding（脚手架式支持结构）已经变得多余，甚至开始拖后腿。这就是为什么，即使客户内部也有支持，通常还是由那些已经看过数百次甚至数千次实施过程的 vendor 或 partner 来协助完成这项工作会更容易。所以，这类工作短期内不会消失，而且会成为很多技术人才——尤其是职业早期人才——的一条很好的发展路径。