【文章标题】：AI、工具与变革
【文章正文】： AI, tools and transformation AI、工具与变革
The typical big American company today has hundreds, and perhaps thousands, of different pieces of software. It has giant ‘big iron’ horizontal systems of record like SAP and Workday, it has hundreds of vertical SaaS applications, and then there are hundreds more workflows, scripts, automations and databases, right down to the 10 meg spreadsheet running a department. Very often, the company doesn’t even know quite how much it has, what’s actually being used, and what it’s paying for. And yet, with all this software, the company is full of boring, repetitive tasks. 如今的典型美国大企业拥有数百甚至数千种不同软件。既有SAP、Workday这类庞大的”重型”横向记录系统，也有数百个垂直SaaS应用，还有数百个工作流、脚本、自动化程序和数据库，直至那些管理部门的10兆电子表格。很多时候，企业甚至不清楚自己拥有多少软件、实际使用哪些、以及具体支付了哪些费用。然而尽管软件如此繁多，企业仍充斥着枯燥重复的工作。
It can be very tempting to think that AI will sweep most of this away. There’s an old joke that an engineer is someone who’ll spend an hour building a tool to automate a task that would take 10 minutes. But with AI, now you can make that tool in five minutes, and you don’t need to be an engineer, and you don’t need to write code. You can just ask the model to make the tool for you, or, more fundamentally, just do the task for you itself. Instead of having to create those tools one at a time, software might be dynamic, generative, free-form, and spontaneous. Massively more tasks can be automated, with massively less software. 人们很容易认为AI将横扫这一切。有个老笑话：工程师就是愿意花一小时开发工具来自动化十分钟任务的人。但有了AI，现在你只需五分钟就能制作那个工具，无需工程师身份，也无需编写代码。你可以直接让模型为你创建工具，或者更根本地，让它直接替你完成任务。软件可能变得动态、生成式、自由形态且自发产生，而无需逐个创建工具。自动化任务将呈指数级增长，所需软件却大幅减少。
If you’re a tool-builder, and everybody in Silicon Valley is a tool-builder, this is intoxicating. But I think it misunderstands where software comes from and how people use it, and I think it misses how companies change. 如果你是个工具建造者（硅谷人人都是），这想法令人陶醉。但我认为这误解了软件的来源与使用方式，也忽视了企业的变革逻辑。
First of all, most people are not tool builders, and most people don’t instinctively think about how their job could be done in a different way. If you spend all your time in the Silicon Valley bubble, it can be easy to forget this, because your entire world is about creating tools that change how things are done. But if you’re a really great matrimonial lawyer, you spend all your day thinking about your cases and your clients, not about what great legal discovery software would do; if you’re a really great enterprise salesperson, you spend all your time thinking about your product and your clients and your competitors, not about how great sales enablement software could make you more productive. 首先，多数人并非工具建造者，也不会本能地思考如何用不同方式完成工作。若你终日身处硅谷泡沫中，很容易忘记这点——因为你的整个世界都围绕着创造改变做事方式的工具。但顶尖的婚姻律师整天思考的是案件和客户，而非法律检索软件；杰出的企业销售员时刻琢磨的是产品、客户和竞争对手，而非销售赋能软件如何提升效率。
Products like Excel try to bridge this problem with on-boarding flows, assistants, and templates - everything you see in ‘File/New’ is a suggestion for what you could do with this. But every one of those templates still became a company, and that’s what I see in things like Claude for X as well - this is helpful, but not the answer. 像Excel这类产品试图通过入门流程、助手和模板来弥合这个问题——“文件/新建”里的每个选项都是使用建议。但每个模板背后仍需要一个公司来创建，这也是我在Claude for X等产品中看到的——这有帮助，但并非解决方案。
Narrowly, that means that the task to be automated might be sitting in plain sight but the people with that task don’t see it. This is what leads to the idea of the ‘forward-deployed engineer’ - someone who is a builder, and knows what AI can build, can ‘just’ walk around a law firm or an architecture office and see the opportunities lying on the table that the lawyer or the architect doesn’t see. (This is also the experience of a lot of people in tech when they were 15, wandering around an internship or their parents’s office - “um, daddy, did you realise you could just do it like this?”). 狭义而言，这意味着待自动化的任务可能显而易见，但执行者却视而不见。这催生了”前置工程师”的概念——具备建造能力且了解AI潜力的人，只需在律所或设计事务所转一圈，就能发现律师或建筑师桌上被忽视的自动化机会。（这也是许多科技从业者15岁在父母办公室实习时的体验——“爸爸，你没发现可以这样做吗？”）
The deeper problem is most of what we’ve automated in the last few decades wasn’t obvious, even if you are a tool-builder, and didn’t have an obvious solution either. We can all think of examples of stuff we use every day where our first reaction was “Why would I want that?” Very often, it’s not obvious that the problem exists, and very often it’s embedded or bundled or hidden inside something else. Equally, even if you can see the problem, or think you can, the right way to fix it often isn’t clear either, and the way to fix it is to redefine it or unbundle it, and working that out is hard. For many successful software companies, there were half a dozen failed attempts that came before and didn’t find quite the right approach or the right problem. 更深层的问题是：过去几十年我们自动化的多数事物，即便对工具建造者也不明显，且解决方案也不明确。我们都能想到日常使用的东西最初让人疑惑”我要这干嘛？“。问题本身常不显而易见，常被嵌套、捆绑或隐藏。即便发现问题，正确解决方式也常不明确，需要重新定义或解构问题——这非常困难。多数成功软件公司背后，都有五六次因未找准问题或方法而失败的尝试。
None of this is solved by making easier to write code - by making it easier to make tools. The hard part is knowing that you need a tool for this in the first place, and then knowing what the tool should do. 简化编码或工具制作并不能解决这些。真正的难点在于首先意识到需要工具，然后明确工具该做什么。
But even once you reach that point, you have to get everybody else to use it, too. Many of the problems, workflows and tasks that we might want to automate touch 50 or 500 people across five different departments, three different systems of record, and four different regulatory regimes. You might have a great idea for doing an accounts payable differently, but you yourself can’t change how everybody in the company does it. That has to be a purchase, and a decision, and an 18-month sales process. 即便突破这些关卡，还需让所有人使用。许多待自动化的问题、工作流和任务涉及五个部门、三套记录系统和四种监管体系的50-500人。你可能有应付账款的新方案，但无法单方面改变全公司的做法。这需要采购决策和长达18个月的销售流程。
Second, all of this means that software is bought or chosen or created on a spectrum from top-down to bottom-up - the company buys SAP and the user makes a spreadsheet - and I think it’s useful to think of this also as a spectrum from institutionalised to improvised. 其次，这意味着软件采购/选择/创建存在自上而下到自下而上的光谱（公司采购SAP vs 员工制作电子表格），我认为将其视为制度化到即兴创作的光谱也很有帮助。
You have tasks that are easy to do in the dedicated tools you already have, whether it’s SAP, Carta or Rippling. These tasks… 有些任务用现有专用工具（如SAP、Carta或Rippling）就能轻松完成。这些任务…