人工智能代码领域的竞争正日趋白热化。

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人工智能代码领域的竞争正日趋白热化。

内容来源：https://www.theverge.com/column/910019/ai-coding-wars-openai-google-anthropic

内容总结：

AI编程工具掀起软件行业变革风暴，开发者与“氛围编程”时代何去何从？

近年来，人工智能技术正以前所未有的速度重塑软件开发领域。自2021年微软与OpenAI合作推出GitHub Copilot以来，AI编程工具已从辅助代码补全的“实习生”，演进为能够独立生成完整原型的高效助手。2025年， Anthropic公司发布的Claude Code工具引发行业震动，其强大的代码生成能力使“AI编写100%代码”成为可能，迅速在开发者社群中掀起热潮。

这场由OpenAI、谷歌和Anthropic主导的“AI代码战争”已进入白热化阶段。各大科技巨头不仅持续升级编程工具，更将AI编码视为核心战略方向。行业数据显示，近98%的受访开发者每周多次使用AI编程工具，硅谷企业甚至将GPU算力访问权限作为人才招聘的竞争优势。英伟达CEO黄仁勋更直言，高薪工程师每年在AI算力上投入25万美元已成为新常态。

随着技术突破，一种被称为“氛围编程”的现象悄然兴起。非专业开发者通过自然语言描述即可生成可用软件原型，这极大降低了编程门槛。然而这种便利也伴随着风险：代码质量隐患、数据安全漏洞以及对传统开发岗位的冲击正引发广泛担忧。

行业变革已反映在就业市场。多家科技公司近期以“AI提升效率”为由进行大规模裁员，Block公司首席执行官杰克·多西在裁员备忘录中明确表示，更小规模的团队借助AI工具“可以做得更多更好”。这种趋势正在引发行业对“软件即服务”商业模式的重新审视，部分观察家甚至提出“SaaS末日”的预警。

面对变革，行业呈现两极分化：专业开发者担忧职业前景，而普通用户仍面临工具使用门槛。为此，企业正推出更易用的产品如Claude Cowork，尝试让AI直接操作用户文件系统。但如何平衡效率与安全、开放与生态控制，仍是待解难题。

目前主流AI编程工具月费集中在20至200美元区间，随着OpenAI等公司推出针对重度用户的中间价位套餐，基础服务的功能边界可能逐步收缩。与此同时，各大厂商正通过生态控制强化用户粘性，行业竞争焦点已从技术突破转向应用生态构建。

这场由AI驱动的编程革命正在重新定义软件创造的方式。无论是专业开发者还是“氛围编程”爱好者，都将在技术浪潮中寻找新的定位。而整个软件产业，也在经历着价值重估与格局重塑的关键时刻。

中文翻译：

这里是《科技回望》（The Stepback），一份每周为您深度解析科技界核心动态的通讯。若想进一步了解AI编程与氛围编程的热潮，请关注大卫·皮尔斯（David Pierce）。《科技回望》将于东部时间上午8点送达订阅用户邮箱。点击此处订阅《科技回望》。

AI编程大战持续升温

OpenAI、谷歌和Anthropic正以迅猛之势重塑软件世界。

缘起

早在人工智能成为热议话题之前，编写代码便已是AI的杀手级应用。2021年春，在“ChatGPT”一词进入大众视野的18个月前，微软首次发布了与开源非营利组织OpenAI合作的首个产品：一款名为GitHub Copilot的工具。它能观察开发者编写代码的过程，并尝试自动补全代码片段。尽管当时它还不够完善，仅处于“受限技术预览”阶段，仍有超过百万开发者注册试用。

大型语言模型显然有望让软件开发变得更简单、更快速。大多数代码结构相对规整、逻辑直接；编程语言通常有极其完善的文档支持；网络上还有海量代码可用于训练模型（尽管获取方式有时存疑）。与从LLM获取的其他信息不同，代码质量只需运行即可验证。最初，一些公司设想，LLM或许能像谷歌的自动补全功能那样，通过预测下一个单词来提升编码速度。但很快，它们便期待这些工具能代劳部分甚至全部编码工作。

多年来，科技行业的公司也一直在探索“低代码”和“无代码”软件的理念。其核心是让用户能自主构建软件，而非面对无穷尽的设置列表和难以理解的菜单。长期以来，这类工具大多较为粗糙：例如Zapier和苹果快捷指令这类超级复杂的工作流构建器，或是Notion和Airtable这类功能强大但学习成本较高的软件。

即便在早期，AI编程工具的商业潜力也已显而易见。开发者人力成本高昂，产品开发周期漫长。任何能帮助企业减少开发人员雇佣或提升开发效率的工具，无疑都能轻易吸引全球软件公司的关注。一旦技术成熟，产品几乎不愁销路。Cursor和Windsurf等公司筹集巨资，试图围绕AI编程工具创业；而OpenAI、谷歌、Anthropic等巨头也开始为开发者打造新产品。

起初，AI编程工具并不可靠。有几年时间，它们或许能补全几行代码，但始终需要人工核查。2023年末，程序员兼博主西蒙·威尔逊（Simon Willison）将LLMs比作“古怪的编程实习生”。他思考着这些实习生会让程序员变得比以往更全能、更强大，还是终将取代他们。

2025年初，Anthropic发布了名为Claude Code的产品，很快让更多人开始紧迫地思考这个问题。

现状

2025年末，Anthropic发布了其Claude大型语言模型的新版本Opus 4.5。根据Anthropic的基准测试，这是当时最优秀的Claude模型，但似乎并未代表AI技术的突破性进展。然而几周后，许多在假期中有空闲的开发者开始用Claude Code测试新模型，几乎都得出了相同的结论：它真的能用。突然间，这个曾经需要精心提示和仔细审查的工具，能将几句话变成一个可运行的原型。Claude Code的创建者鲍里斯·切尔尼（Boris Cherny）宣称自己已完全让AI编写所有代码。“我和所有人一样惊讶，”他今年早些时候告诉《The Verge》。以一种对编程工具而言似乎不可能的方式，Claude Code迅速走红。

Claude Code或许点燃了软件世界的想象，但Anthropic的竞争对手并未落后。OpenAI的Codex于2025年Claude Code发布几个月后推出，经过多次更新，已成为强大且受欢迎的编程工具。谷歌为其Gemini模型推出了命令行界面，并最近在其AI Studio应用中增加了更多编程功能。

日益明显的是，AI编程似乎正成为首个真正主流的AI应用场景——更不用说它可能是首个潜力巨大的AI商业模式。Claude Code的走红与Anthropic收入的爆发式增长同步；OpenAI的一位高管近期要求团队停止“支线任务”，专注于与Anthropic和Claude Code竞争。据报道，OpenAI和Anthropic都计划今年上市，这意味着两家公司需要向投资者展示它们筹集和消耗的数十亿美元资金的价值。而目前看来，编程似乎是它们最看好的方向。

平心而论，这猜测不无道理。硅谷的公司突然发现员工竞相使用最多的AI计算资源（tokens），将GPU访问权限作为招聘筹码，并公开炫耀AI开支。英伟达CEO黄仁勋近期表示，他会担心任何高薪工程师每年在AI tokens上的花费低于25万美元。尽管开发者担忧AI编程工具可能终结他们的职业和生计，但争相尽快拥抱这些工具的竞赛已然开始。2025年的一项研究发现，98%的受访者表示他们“每周多次”使用AI编程工具。

不仅如此。2025年2月，AI行业资深人士安德烈·卡帕西（Andrej Karpathy）提出了“氛围编程”（vibe coding）一词。“我在做一个项目或网页应用，”他在X上写道，“但这其实不算编程——我只是看看、说说、运行、复制粘贴，然后它大多就能运行。”

遗憾的是卡帕西没想出一个更抓人的短语，因为“氛围编程”这个词和现象都留了下来：许多不会甚至不能写代码的人突然通过提示词做出了可用的软件。对其中许多人（他们原本可能只会做幻灯片或Figma原型）来说，一个勉强能用的原型已足够，而这些编程工具已被证明完全能构建出这样的原型。但氛围编程也有风险，无论是糟糕代码可能引发的问题，还是赋予这些工具访问电脑和数据的权限所带来的隐患。当你能验证输出时信任系统是一回事，当你连它的语言都不懂时信任它则是另一回事。

未来走向

软件开发者的危机才刚刚开始。硅谷的公司正以数千人为规模裁员，通常将AI列为原因。“使用我们正在构建的工具，一个规模小得多的团队能做得更多、更好，”Block CEO杰克·多西（Jack Dorsey）在一份宣布裁员40%的备忘录中写道，“而且智能工具的能力每周都在加速提升。”在Block和许多其他公司，AI可能至少部分掩盖了疫情期间过度招聘的问题，但科技行业显然将AI视为提升生产力——并减少人力——的途径。

随着AI编程工具持续改进，它们也可能重塑软件行业的其他领域。既然Claude Code能按你的需求定制软件，为何还要高价购买他人的产品？有人称此为“SaaS末日”（SaaSpocalypse），预测软件价值评估方式将发生根本性重构。另一些人则认为我们将迎来新一代成功的初创企业，它们将以AI原生的方式处理一切。还有人认为这一切言过其实，Salesforce等公司仍将安然无恙。无论结果如何，这个已发展到难以想象的高度和估值的软件产业，在许多人看来正突然变得根基不稳。

开发者光谱的另一端是氛围编程者。对大多数人来说，即使当前最简单的AI编程工具也过于复杂：它们要求你阅读代码、需要终端访问权限、提出许多几乎无人能答的问题。AI编程仍存在大量漏洞、重大隐私疑虑，以及太多恶意行为者可能利用的途径。

通过Claude Cowork等产品，Anthropic已开始尝试让Claude Code的技术更易用、更亲民——你只需授权它访问电脑上的一些文件，让它开始工作。Perplexity Computer等产品则在探索是否能让LLMs访问用户设备上的所有内容，使AI工具能整理文件、回复信息，甚至代购商品。底层技术开始奏效，但人们该如何使用它、甚至是否愿意使用，仍不明朗。

顺便一提

延伸阅读

英文来源：

This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on the AI coding and vibe-coding booms, follow David Pierce. The Stepback arrives in our subscribers’ inboxes at 8AM ET. Opt in for The Stepback here.
The AI code wars are heating up
OpenAI, Google, and Anthropic are eating the software world alive.
How it started
Writing code was a killer app for AI even before anyone was really talking about AI. In the spring of 2021, 18 months before the world knew the word “ChatGPT,” Microsoft debuted the very first product of a partnership with a nonprofit called OpenAI: a tool called GitHub Copilot that watched developers as they wrote code and tried to autocomplete snippets and lines for them. It wasn’t all that good, and it was only a “restricted technical preview,” but more than a million developers signed up to try it anyway.
Large language models seemed obviously poised to make software development even simpler and even faster. Most code is relatively structured and straightforward; coding languages are generally extremely well-documented; and a vast amount of code is available online for use in training models (albeit via sometimes dubious means). Unlike so much other information you might get from an LLM, you can also check the quality of code just by trying to run it. At first, a few companies figured, LLMs might be able to make writing code faster by predicting the next word the way Google’s autocomplete might. But pretty soon, they hoped, it might be able to do some of the coding for you. Maybe even all of it.
For so many years, companies around the tech industry had also pursued the idea of “low code” and “no code” software. Rather than offering users endless lists of settings and unparseable menus, the idea was to effectively let people build software themselves. For a long time, this was pretty hacky: you got things like Zapier and Apple Shortcuts, which were effectively super-complex workflow builders; or you got software like Notion and Airtable, which were immensely flexible at the cost of being pretty hard to figure out.
Even in those early days, it was also obvious why AI coding tools might one day be a good business. Developers are expensive; product creation takes a long time. Any tool that might mean companies could hire fewer developers, or help developers be more productive, would surely be an easy pitch to software companies the world over. If the tech ever worked, the products would practically sell themselves. Companies like Cursor and Windsurf raised huge sums of money to try and build companies around AI coding tools, while OpenAI, Google, Anthropic, and others began building new products for developers.
At first, AI coding tools were not to be trusted. For a couple of years, they could maybe complete a few lines of code, but always needed to be checked. In late 2023, Simon Willison, a programmer and blogger, called LLMs “weird coding interns.” He wondered whether these interns would make coders more versatile and powerful than ever, or eventually begin to replace them.
In early 2025, Anthropic released a product called Claude Code that would soon make that question much more urgent for many more people.
How it’s going
In late 2025, Anthropic released a new version of its Claude LLM, called Opus 4.5. According to Anthropic’s benchmarks, it was the best Claude model yet, but didn’t seem to represent some earth-shattering advancement in AI technology. A few weeks later, though, a lot of developers with a few free hours during the holidays began to test the new model in Claude Code, and almost universally seemed to arrive at the same conclusion: it works. Suddenly, the tool you previously had to carefully prompt and carefully review could turn a few sentences into a working prototype. Boris Cherny, the creator of Claude Code, professed to already having AI write 100 percent of his code. “It was just as surprising for me as it was for everyone else,” he told The Verge earlier this year. In a way that seemed impossible for a coding tool, Claude Code went viral.
Claude Code may have captured a lot of the software world’s imagination, but Anthropic’s competition hasn’t been far behind. OpenAI’s Codex, which launched in 2025 a few months after Claude Code, has gotten a series of updates and is also a powerful and popular tool for writing code. Google rolled out a command line interface for its Gemini model and has recently been putting more coding features into its AI Studio app.
Increasingly, AI coding seems like the first truly mainstream AI use case — not to mention the first potentially great AI business. The Claude Code moment coincided with an absolute explosion in revenue for Anthropic; one of OpenAI’s top executives recently told her team to stop doing “side quests” and focus instead on competing with Anthropic and Claude Code. Both OpenAI and Anthropic are reportedly planning to go public this year, which means both companies will need something to show for the billions they’ve raised in capital, and the billions they’ve burned on compute. It seems everyone’s best idea is writing code.
In fairness, it looks like a pretty reasonable guess. Companies around Silicon Valley are suddenly seeing employees compete to use the most tokens, using GPU access as a recruiting tool, and bragging publicly about their AI bills. Nvidia CEO Jensen Huang recently said he’d worry about any highly paid engineer who wasn’t spending $250,000 a year on AI tokens. Even as developers fear AI coding tools might spell the end of their careers and livelihoods, the race is on to embrace them as quickly as possible. One 2025 study found that 98 percent of respondents said they used AI coding tools “several times a week.”
It’s not just developers, either. In February of 2025, Andrej Karpathy, a veteran of the AI industry, coined the term “vibe coding.” “I’m building a project or webapp,” he wrote on X, “but it’s not really coding - I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works.”
It’s a shame Karpathy didn’t come up with a catchier phrase, because vibe coding stuck. The name as well as the phenomenon: lots of people who didn’t or even couldn’t write code were suddenly prompting their way to workable software. For many of those people, who might otherwise have made slide decks or Figma mockups, a barely functional prototype was plenty, and these coding tools have proven more than capable of building barely functional prototypes. Vibe coding does come with risks, though, both in terms of the problems bad code can cause and the risks you run by giving these tools access to your computer and your data. It’s one thing to trust the system when you can verify its output, another to do so when you can’t speak its language.
What happens next
The software developer crisis is only just beginning. Companies around Silicon Valley are laying off employees by the thousands, usually citing AI as the reason. “A significantly smaller team, using the tools we’re building, can do more and do it better,” Block CEO Jack Dorsey wrote in a memo announcing 40 percent of the company was being laid off. “And intelligence tool capabilities are compounding faster every week.” In Block’s case and many others, AI is likely at least in part just a cover for pandemic-era overhiring, but the tech industry is clearly set on AI as a way to enhance productivity — and reduce headcount.
As AI coding tools continue to improve, they might also remake the rest of the software business. Why pay a fortune for someone else’s software when Claude Code could build it for you, exactly the way you want it? Some are calling this the SaaSpocalypse, and predicting a fundamental rethinking of the way we value software. Others think we’re due for a new generation of successful startups, which offer AI-native ways to do everything. Still others think it’s all overblown and Salesforce will be just fine. Whatever the outcome, the software industry, which has grown to such unthinkable heights and valuations, feels to many like it’s suddenly on shaky ground.
On the other end of the developer spectrum are the vibe coders. For most people, even the simplest current AI coding tools are too much. They make you read code; they require Terminal access; they ask a lot of questions hardly anyone should be expected to know how to answer. AI coding still comes with plenty of bugs, big privacy questions, and too many ways in which bad actors are able to exploit them both.
With products like Claude Cowork, Anthropic has begun to see if it can make Claude Code’s technology a little more accessible and less intimidating — you just give it access to a bunch of files on your computer and let it go to work. Products like Perplexity Computer are exploring whether people might give LLMs access to everything on their devices, allowing the AI tools to organize files, answer messages, even buy things on their behalf. The underlying tech is beginning to work, but it’s not at all clear how people are supposed to use it, and whether they’ll even want to.
By the way

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