OpenAI is building AI agents for everything. Will everyone use them?
OpenAI is building AI agents for everything. Will everyone use them?
OpenAI 正在为一切事物构建 AI 智能体。每个人都会使用它们吗？
How much control are you willing to give an LLM over your digital life? Getting the most value from a model means giving it the keys. For a control freak or the AI-hesitant, it seems like a lot. For Andrew Ambrosino, the lead engineer for OpenAI’s desktop app, it’s the only way to test the future, which is why that app now has access to, and control over, his inbox, his Slack account, his phone, apps like Notion and Figma, and more. 你愿意让大语言模型（LLM）在多大程度上掌控你的数字生活？要从模型中获得最大价值，就意味着要交出“钥匙”。对于控制狂或对 AI 持怀疑态度的人来说，这似乎代价巨大。但对于 OpenAI 桌面应用的主管工程师 Andrew Ambrosino 而言，这是测试未来的唯一途径。正因如此，该应用现在可以访问并控制他的收件箱、Slack 账号、手机，以及 Notion 和 Figma 等应用程序。
“If I’m asking it to write a document, is there a possibility that it’s going to pull from a private DM on that subject and not know that it’s not supposed to share some info? Yes,” Ambrosino told TechCrunch. “I’ll do it for the job. I will take the personal hit here and there if I have to. And I haven’t had to.” “如果我让它写一份文档，它有没有可能从相关的私人私信中提取信息，却不知道有些信息是不该分享的？有可能，”Ambrosino 告诉 TechCrunch。“为了工作，我愿意这么做。如果有必要，我愿意承担一些个人风险。不过目前还没发生过这种情况。”
Ambrosino works on OpenAI’s biggest bet, ChatGPT Work, which was released last month and is available on the company’s lowest subscription tier, for $20 a month. The product is intended to allow white-collar workers to field AI agents — hooking LLMs up to the digital workflows used by accountants, investors, doctors, and everyone else whose day-to-day is dominated by their computer. Ambrosino 负责 OpenAI 的重头戏——ChatGPT Work。该产品于上个月发布，包含在公司每月 20 美元的最低订阅档位中。这款产品的目标是让白领员工能够部署 AI 智能体，将大语言模型接入会计师、投资者、医生以及其他日常工作离不开电脑的专业人士的数字工作流中。
OpenAI’s marketing copy puts the goal succinctly: A world where “where [artificial] intelligence goes beyond answering questions to helping everyone turn their biggest ideas into reality.” For software developers, that shift is already happening, but it’s been slow to spread to other departments. OpenAI 的营销文案简洁地阐述了这一目标：一个“人工智能不仅能回答问题，还能帮助每个人将最宏大的想法变为现实”的世界。对于软件开发者来说，这种转变已经发生，但在其他部门的普及速度却很慢。
ChatGPT Work is a modified version of the company’s Codex coding tool. It’s meant to give non-engineers a version of the same functionality that software engineers already get from agents: an AI tool that doesn’t just answer questions, but completes multistep projects on its own. ChatGPT Work 是该公司 Codex 编程工具的修改版。它的目的是让非工程师群体也能获得软件工程师通过智能体所享有的功能：一种不仅能回答问题，还能自主完成多步骤项目的 AI 工具。
“In this new factor, ChatGPT can actually do entire, very complicated tasks for you all autonomously in a way that is delightful and safe,” Thibault Sottiaux, who leads OpenAI’s core product work, including Work, told TechCrunch. “It’s the very mission of OpenAI — to bring everyone along.” “在这一新模式下，ChatGPT 实际上可以完全自主地为你完成整个非常复杂的任务，而且过程既令人愉悦又安全，”负责 OpenAI 核心产品（包括 Work）的 Thibault Sottiaux 告诉 TechCrunch。“这正是 OpenAI 的使命——让每个人都能参与其中。”
Commercially, that matters a lot. Agents that work for longer stretches burn through more tokens, which makes them more lucrative for OpenAI on a per-user basis. Reaching new professions is crucial — not just for OpenAI, but for the industry at large. If coding has proven lucrative territory for AI labs, it’s still a tiny subset of the professional work AI tools need to enable if these companies are to justify their massive investment in training and computation. 从商业角度来看，这一点至关重要。运行时间更长的智能体会消耗更多 Token，这使得它们对 OpenAI 而言在单用户基础上更具盈利能力。触达新的职业领域至关重要——不仅对 OpenAI 如此，对整个行业也是如此。如果说编程已被证明是 AI 实验室的盈利领域，那么它在 AI 工具需要赋能的专业工作中仍只占极小一部分，而这些公司必须通过扩展业务来证明其在训练和计算方面巨额投资的合理性。
While labs have been focused on software engineers, vertical-specific competitors like Harvey (for law) and Clay (for sales) have been chasing those customers with a model-agnostic approach, meaning they’ll plug in whichever AI works best at the time. Industry analysts see this as one of the major challenges facing OpenAI and its competitors. 虽然实验室一直专注于软件工程师，但像 Harvey（针对法律）和 Clay（针对销售）等垂直领域的竞争对手，正以“模型无关”的方式争夺这些客户，这意味着他们会接入当时表现最好的 AI 模型。行业分析师认为，这是 OpenAI 及其竞争对手面临的主要挑战之一。
“If the labs cannot rapidly get ahold of the key complementary assets needed to scale AI in the market, value will accrue elsewhere,” Christian Catalini wrote on a16z’s “It’s time to build” blog. “如果实验室不能迅速掌握在市场上扩展 AI 所需的关键互补资产，价值就会流向其他地方，”Christian Catalini 在 a16z 的“It’s time to build”博客中写道。
Making the AI apps work for people who aren’t software engineers requires more hand-holding. OpenAI’s non-engineering workforce, like the communications and finance teams, started using Codex “at a time that it was actively hostile to them—asking them about code and showing them, ‘oh, you have an empty diff for this thing,’” Ambrosino said, referring to a technical readout meant for software changes. “So, we started to make it more general purpose between February and now.” 要让 AI 应用为非软件工程师所用，需要更多的引导。Ambrosino 说，OpenAI 的非工程部门员工（如公关和财务团队）开始使用 Codex 时，“它对他们非常不友好——总是问他们代码相关的问题，并显示‘哦，这个东西的差异对比（diff）为空’”（他指的是一种用于软件变更的技术输出）。“因此，从二月到现在，我们开始让它变得更加通用。”
An OpenAI-backed study found that in June, 98% of OpenAI employees were using Codex, but just 17% of organizational subscribers and less than 1% of individual subscribers were using the agentic coding tool. That difference between near total adoption inside the company and negligible adoption outside it is the challenge and opportunity for the company. 一项由 OpenAI 支持的研究发现，今年 6 月，98% 的 OpenAI 员工在使用 Codex，但只有 17% 的组织订阅用户和不到 1% 的个人订阅用户在使用该智能体编程工具。公司内部近乎全面的采用率与外部微不足道的采用率之间的差距，既是挑战，也是机遇。
“The more value and the more utility that we generate for users, the more they will be willing to also pay for some part of that utility, and that’s how we’ve always seen ChatGPT as well,” Sottiaux said. “You sit there and you’re like, ’of course I want to pay $20 bucks a month for this,’ because the value that you get is so much more.” “我们为用户创造的价值和效用越多，他们就越愿意为这些效用付费，这也是我们一直以来看待 ChatGPT 的方式，”Sottiaux 说。“你会坐在那里想，‘我当然愿意每月付 20 美元用这个’，因为你从中获得的价值远超于此。”
How to make AI intuitive 如何让 AI 变得直观
To understand that disconnect, it helps to understand what OpenAI’s engineers are building. Every LLM requires what engineers call a “harness” — the software wrapped around a model that decides what information it sees, which tools it can use, and how it presents its answers back to you. If you want that model to do stuff — to become an agent — the harness gives it tools and instructions for using them on long-term tasks. 要理解这种脱节，首先需要了解 OpenAI 的工程师们正在构建什么。每个大语言模型都需要工程师所说的“外壳”（harness）——即包裹在模型周围的软件，它决定了模型能看到什么信息、能使用哪些工具，以及如何向你呈现答案。如果你想让模型做事情——即成为一个智能体——这个“外壳”就会为它提供工具和指令，以便在长期任务中使用这些工具。
For developers, a command-line interface (CLI) that enabled LLMs to code was enough to change the way software was built and deployed. But most people aren’t using CLIs; there’s a reason Windows replaced DOS. An agentic product that goes beyond software engineering is “going to be something that plays with the messy world of your life and your tools and websites that were built in 1995 and never updated,” Ambrosino told TechCrunch, explaining that the experiences his team is building are vital to expanding access to useful AI. 对于开发者来说，一个能让大语言模型进行编程的命令行界面（CLI）足以改变软件的构建和部署方式。但大多数人并不使用命令行；Windows 取代 DOS 是有原因的。Ambrosino 告诉 TechCrunch，一个超越软件工程的智能体产品，“将是能够处理你生活中混乱世界、你的工具以及那些 1995 年建成后从未更新过的网站的东西”，他解释说，他的团队正在构建的体验对于扩大有用 AI 的普及至关重要。
Consider apps like Claude Code and Codex: They unleashed “vibe coding” by abstracting away all the actual software writing, and letting users just tell the model what they want in a program. Now, OpenAI wants to make functionality found in tools like OpenClaw, which coders use to put LLMs to work, as easy as prompting. “Without these products in front of the model, experts would know how to get the same results, but you wouldn’t get to a billion people using the thing,” Ambrosino said. 以 Claude Code 和 Codex 等应用为例：它们通过抽象掉所有实际的软件编写过程，让用户只需告诉模型他们想要什么样的程序，从而释放了“氛围编程”（vibe coding）。现在，OpenAI 希望让程序员用来驱动大语言模型的 OpenClaw 等工具中的功能，变得像输入提示词一样简单。“如果没有这些位于模型前端的产品，专家们固然知道如何获得同样的结果，但你无法让十亿人使用它，”Ambrosino 说。
That trade-off between what power users need and what mainstream adoption requires plays out in internal debates at OpenAI, where some employees argue that a button is unnecessary if users can just a 这种在高级用户需求与主流采用需求之间的权衡，在 OpenAI 的内部辩论中不断上演。一些员工认为，如果用户可以直接通过……（原文截断）