Julie Yack

Every few years, technology gives us a new label.每隔几年，技术就给我们一个新标签。

Client/server. Cloud. Mobile. Low code. AI.客户/服务器。云端。移动。低代码。AI。

We spend years debating what each one means, who it’s for, and whether it’s going to replace whatever came before it. Then enough time passes that we can finally step back and see where it fits in the bigger story.花上几年争论每个标签的意义、受众，以及它是否会取代之前的一切。时间够了，回头再看，才知道它在更大的故事中处在什么位置。

I think we’re finally at that point with low code.我想，对低代码，我们终于到了那个节点。

For years, low code was treated as the breakthrough. The idea that people could build business solutions without being professional programmers felt like a dramatic shift.多年来，低代码被视为突破。非专业程序员也能构建业务方案，感觉像巨大的转变。

It was.确实是。

Just maybe not in the way we thought.只不过，可能不是我们想的那样。

Looking back, I don’t think low code was the revolution. It was the evolution.回头看，我不觉得低代码是革命。它是演进。

For as long as developers have been writing software, other people have been solving business problems. They’ve been improving customer experiences, redesigning processes, resolving conflicts, making decisions, managing risk, building teams, and helping organizations change. Sometimes technology was part of the solution. Sometimes it wasn’t. But the work itself—the problem solving—has never belonged exclusively to people who write code.从开发者写软件开始，其他人就在解决业务问题。改善客户体验、重新设计流程、化解冲突、做决策、管理风险、组建团队、帮助组织变革。有时技术是方案的一部分。有时不是。但解决问题这种工作本身，从不只属于写代码的人。

People solve problems.人解决问题。

Technology helps.技术帮忙。

That has always been true.一直都这样。

The challenge was that implementation was expensive. Turning an idea into working software required specialized skills, specialized tools, and specialized people. Low code changed that equation. It removed friction. It invited more people into the process.挑战在于实现很贵。把想法变成能用的软件，需要专门的技能、工具和人。低代码改变了等式。它去除了摩擦。它让更多人参与进来。

It shortened the distance between the person who understood the problem and the person who could implement it.它缩短了理解问题的人与能实现它的人之间的距离。

That wasn’t a small achievement. It changed who could participate.那不是小成就。它改变了谁可以参与。

Now AI is changing the equation again.现在AI又在改变等式。

The conversations I’ve been having aren’t about code. They’re about reasoning. Judgment. Context. Communication. Desired outcomes.我最近参与的讨论，不关于代码。它们关于推理、判断、上下文、沟通、期望的结果。

Prompting is a good example.提示就是一个好例子。

People talk about prompting as though it’s an entirely new skill. I don’t see it that way.人们讨论提示，好像它是个全新技能。我不这么看。

For decades we’ve been communicating intent through conversations, whiteboards, requirements documents, emails, user stories, workshops, and design sessions. A prompt is another way to do that. The medium is different. The goal isn’t.几十年来，我们通过对话、白板、需求文档、邮件、用户故事、工作坊、设计讨论来传达意图。提示是另一种方式。媒介不同。目标没变。

That’s why I think we’re asking the wrong questions. We spend a lot of time asking what AI can do.这就是为什么我觉得我们在问错问题。我们花很多时间问AI能做什么。

Can it write code?它能写代码吗？

Can it build an agent?它能建智能体吗？

Can it summarize meetings?它能总结会议吗？

Those are interesting capabilities. They’re just not the outcome anyone is ultimately trying to achieve.这些能力很有意思。只是没人最终想追求这些结果。

Nobody wakes up wanting a meeting summary. They want faster decisions.没人一早醒来想要会议纪要。他们想要更快的决策。

Nobody wants an AI-generated email. They want better communication with customers.没人想要AI生成的邮件。他们想要和客户更好的沟通。

Nobody wants an agent. They want fewer repetitive tasks, more time for meaningful work, and better business results.没人想要智能体。他们想要少些重复任务，多点时间做有意义的事，更好的业务成果。

(***ok, so maybe we want an agent because it can be cool to have an agent, but that’s a whole other blog post***)（好吧，可能我们也想要个智能体，因为有个智能体很酷，但那是另一篇博客的事了）

The capability isn’t the point. The outcome is. Maybe that’s why I’ve never really thought of myself as a low-code person.能力不是关键。结果才是。可能这就是为什么我从不觉得自己是个低代码人。

I’ve spent my career helping organizations solve business problems. Sometimes that meant implementing software. Sometimes it meant facilitating a workshop. Sometimes it meant helping people adopt change. Sometimes it meant asking uncomfortable questions before anyone started building anything.我的职业生涯就是帮组织解决业务问题。有时是实施软件。有时是引导工作坊。有时是帮人们接受变化。有时是在任何人开始构建之前，先问不舒服的问题。

The technology changed. The work didn’t.技术变了。工作没变。

AI is revolutionary. Whether it’s the revolution or simply the next step in a longer story, none of us can know yet.AI是革命性的。它到底是革命，还是更长故事里的下一步，我们现在还不知道。

What I do know is this. The organizations that succeed won’t be the ones that can demonstrate the most AI capabilities. They’ll be the ones that consistently create the best outcomes.我所知道的是：成功的不将是展示最多AI能力的组织。而是持续创造最好结果的那些。

I’d bet THE revolution is what happens once AI is no longer a novelty.我赌，真正的革命发生在AI不再是新奇事物的那一天。