亚马逊已告知其工程师要最大化价值，而非令牌使用量，理由是担心人工智能成本和复杂性不断上升。亚马逊周二通过一份发给工程团队的备忘录公开了这一战略转变，概述了在人工智能时代其软件开发工程师角色的变化。“我们最多产的工程师已经证明，无论是开发人员的角色还是他们的产出，都不是由人工智能的使用来定义的，”亚马逊副总裁兼资深工程师特克·特科维茨在备忘录中写道。
Maximize value, not token usage, Amazon has told its engineers, citing concerns about rising AI costs and complexity. Amazon made the strategy shift public on Tuesday in a note to engineering teams outlining the changing role of its software development engineers in the age of AI. “Our most prolific engineers have demonstrated that neither the developer role nor their output is defined by the use of AI,” Amazon VP and distinguished engineer Terk Terkowitz wrote in the note.
“我们现在处于‘文艺复兴型开发者’的时代，将人工智能工具与人类判断力和领域专业知识相结合，构建全新的事物。”换言之，亚马逊希望其开发者使用人工智能，但消耗令牌并不等同于完成有用的工作。备忘录没有根据人工智能的使用方式来定义开发者角色，而是聚焦于变化不那么快的方面：为客户和业务交付有用软件和成果的需求。
“We're now in the era of the Renaissance Developer, blending AI tools with human judgment and domain expertise to build entirely new things.”In other words, Amazon wants its developers using AI, but burning through tokens isn't the same thing as getting useful work done. Rather than define the developer role by how AI is used, the memo focuses on what isn't changing so fast: the need to deliver useful software and results for customers and the business.
“很难以一种经得起时间考验的方式，定义什么是良好的 AI 驱动工程实践，”备忘录继续说道。“随着我们演进 SDE（软件开发工程师）角色……我们决定关注那些没有改变的东西……重要的结果没有变，即使投入、工具和技术的变化速度比以往任何时候都快。”对当下的软件开发者而言，这意味着 AI 输入指标——即使亚马逊在“令牌最大化”团队中看到了一些与生产力和交付提升相关的迹象——并非亚马逊视为衡量开发者时间和资源良性使用的标准。
“It is difficult to define, in a way that will stand the test of time, what good AI powered engineering practices look like,” the memo continues. “We have decided to focus on what is not changing as we evolved the SDE roles … the outcomes that matter aren’t changing, even if the inputs, tools, and techniques are changing faster than ever.”What that means for software developers in the present moment is that AI input metrics, even if Amazon has seen some correlation with increased productivity and delivery on tokenmaxxing teams, aren’t what Amazon sees as a measurement of good use of developer time and resources.
“我们都知道这些指标有多么深刻的缺陷，主要是因为它们与重要的事物脱节，”备忘录辩称。
“We are all aware of how deeply flawed these metrics are, primarily because they are disconnected from what matters,” the memo argues.
备忘录继续指出：“如果将这些指标作为目标而非衡量标准使用，可能会导致负面结果，增加成本，并增加复杂性”，指的是“token最大化”带来的成本以及过于复杂的代码，这与亚马逊“发明与简化”的使命背道而驰。亚马逊发言人证实，该备忘录旨在劝阻“token最大化”行为，并引用了AWS首席执行官马特·加曼6月份的言论，他在其中鼓励开发者在合理使用AI工具进行软件开发时，衡量结果而非token消耗。
“[U]sing these metrics could, if used as a target instead of a measure, drive negative outcomes, increasing costs, and increasing complexity,” the memo continues, referring to tokenmaxxing costs and overly complex code that’s at odds with Amazon’s mission to “invent and simplify.”An Amazon spokesperson confirmed that the memo’s intent was to discourage tokenmaxxing, pointing us to comments from AWS CEO Matt Garman from June in which he encouraged developers to measure outcomes, not token consumption, in making proper use of AI tools for software development.
亚马逊还希望其开发者更多地思考AI如何帮助“改善客户交付”以及业务部门的工作，而不仅仅是试图找个地方塞进AI来证明它对他们有用。备忘录点名批评了一些工程团队“与客户和业务的联系变得更少了”，并表示那些更投入其产品和业务角色的团队“能够最大程度地利用AI和智能体软件开发”，实质上是在呼吁更多团队采取类似的方法。
Amazon also wants its developers thinking more about how AI can help “improve delivery for customers” and business units, not just trying to find a place to stick it to prove it's working for them. The memo calls out some engineering teams who’ve “become less connected to their customers and business,” and says teams that are more engaged with their products and business roles “are able to take the most advantage of AI and agentic software development,” in essence calling for more teams to take a similar approach.
备忘录称：“如果你的工作无法从当前的AI工具中受益，这是一个发现，而非失败。能够解释AI在哪些方面尚无法帮助其工作的工程师，展现了我们所期望的判断力。”亚马逊在备忘录中的立场与微软8月份对其内部开发团队的表态惊人地相似，甚至连强调关注为客户和业务带来的回报、而非最大化投入这一点都如出一辙。
“If your work does not benefit from current AI tooling, that is a finding, not a failing,” the memo said. “An engineer who can explain where AI does not yet help their work is demonstrating the judgement we are asking for.”Amazon's take in the memo is starkly similar to what Microsoft told its own internal development teams in August, right down to stressing a focus on returns for customers and business instead of maximizing input.
微软执行副总裁杰伊·帕里克对开发者表示：“‘Token最大化’不是我们要优化的目标。我希望我们所有人都专注于最大化能为客户和业务带来实质性推动的成果。”由此看来，“到处塞AI看看哪里管用”这种整合技术的方法，似乎已写在墙上（注：意指结局已定、行将结束）。
"Tokenmaxxing is not what we are optimizing for," Microsoft EVP Jay Parikh told developers. "I want all of us focused on maximizing outcomes that move the needle for our customers and our business." With that, the writing seems to be on the wall for the throw-AI-at-everything-and-see-where-it-sticks approach to integrating the tech.
当这两家体量如此庞大的公司开始质疑 AI token 消耗是否是衡量其数千名软件工程师生产力的有用指标时，世界其他地区可能很快就会开始“小口啜饮”这些 token，而不是“大口吞咽”了。要么，我们很快就会看到更多企业开始接受依赖“足够好”的开放权重模型的理念，这些模型能以昂贵替代方案的一小部分成本处理许多任务——Garman 早在 6 月就曾为根据任务选择高性价比模型提出过类似论点。如果你是个泡沫，这种做法看起来非常像一根针。®
When two companies that large start to question whether AI token consumption is a useful measure of productivity for their thousands of software engineers, it's possible the rest of the world will soon start sipping those tokens instead of chugging them. That, or we'll soon see even more enterprises begin to embrace the philosophy of relying on "good enough" open-weight models that can handle many tasks at a fraction of the cost of more expensive alternatives – Garman made a similar case for choosing cost-effective models based on the task back in June. If you're a bubble, that approach looks an awful lot like a pin. ®