有一个极其简单的测试，可以用来判断一家公司的 AI 强制令是否经过深思熟虑，还是由脱离实际的蠢蛋强行推出的：当工程师记录并证明 AI 让某项任务变得更糟时，会发生什么？他们会被认真对待，还是被边缘化、最终被逼走？巧合的是，本周亚马逊发布了一篇由 Terk Terkowitz 撰写的论述，他是该公司的副总裁 / 资深工程师 / 独立贡献者技术职业阶梯的“最终 BOSS”。
There's a ridiculously simple test you can use to figure out whether AI mandates at a given company are well-considered, or are being shoved out the door by out-of-touch buffoons: What happens when an engineer documents that AI made a task worse? Are they taken seriously, or are they marginalized and eventually managed out? Conveniently, this week Amazon published a treatise by Terk Terkowitz, a VP/Distinguished Engineer/Final Boss of Their Independent Contributor Technical Career Track, on the role of the developer in the age of AI.
这篇文章原本是 9 月发给软件工程师及其管理者的内部备忘录，对于一份听起来如此自信的文件来说，这种发布滞后颇耐人寻味。它也极其精准地映射出其他组织正在挣扎的问题。我认为这是一份好文件，但我忍不住要用一种略带愤世嫉俗的眼光来看待它。我把它视为一种试图让软件工程师这个职业的未来显得不那么黯淡的尝试。而对许多人来说，眼下的前景确实一片惨淡。
It was originally an internal missive sent to their software engineers and their managers back in September, which is an interesting lag for a document that sounds this confident. It also maps exceedingly well to what other organizations are struggling with. I think it's a good document, but I can't help but view it with a somewhat cynical eye. I see it as an attempt to make the future of the profession of software engineering feel less bleak. And it's feeling mighty bleak for a lot of folks right now.
背景是什么？这篇论述发布于剧烈动荡之际。科技行业向来不陌生变革（通常凌晨 3 点传来寻呼机响声便预示着变革），但当前世界的“AI 化”让我们许多人感觉，这从根本上区别于以往的革命。大家对职业前景感到恐慌。“我该不该放弃科技行业去种地？”是一个真诚的问题，已有好几个人问过我。我也不知道！科技圈本身就是一场“山羊牛仔竞技”（混乱无序的局面），所以如果你去种地反而占优？
What's the context? This treatise comes at a time of dramatic upheaval. Tech as an industry is no stranger to change (usually at 3AM, heralded by the pager), but something about the current AI-ification of the world strikes many of us as fundamentally dissimilar from previous revolutions. Folks are scared about their career prospects. "Should I give up tech and get into farming?" is a sincere question multiple people have asked me. I don't know! Tech is already a goat rodeo, so you've got a leg up if you do?
这种焦虑并非理论上的。5 月，亚马逊明智地关闭了 KiroRank，这是一个由员工自建的“烧钱排行榜”，按 Token 使用量对人进行排名，随后发生了显而易见的事：人们制造垃圾任务来攀升排名。这现在被称为“Token 刷榜”，Terkowitz 的论述专门点名批评这与“节俭”背道而驰。Meta 同一周也对“Claude 经济学”及其 8.5 万名员工做了同样的事。
This anxiety isn't theoretical. In May, Amazon wisely shut down KiroRank, an employee-built cash incineration leaderboard that ranked people by token usage, after the obvious thing happened: people spun up junk tasks to climb the ranks. This is now called "tokenmaxxing," and the Terkowitz treatise specifically calls it out as being at odds with "frugality." Meta did the same thing with "Claudenomics" and 85K employees that same week.
据报道，亚马逊本周又宣布裁员 250 人。我无法断定这些事情有关联。但我可以告诉你，读过这份备忘录的每一位工程师都认为它们有关。
And Amazon reportedly announced another 250 job cuts this week. I can't tell you that these things are related. But I can tell you that every engineer who read the memo assumes that they are.
备忘录里写了什么？这份文件包含许多精彩内容。我对亚马逊首席工程师群体怀有极高的敬意，无论是个人层面还是职业层面；我听说这种敬意可能并非相互的，但那也没关系。按他们的标准，我是一名“失足工程师”，跑去马戏团当了个三流小丑。Terkowitz 的备忘录强调客户成果和工程判断力，这两样东西我绝不会在短期内委托给 AI。
What's the thing say? This document contains a lot of great stuff. I have a tremendous level of respect, both personal and professional, for Amazon's Principal Engineering community; I'm led to understand that that respect may not be reciprocated, but that's okay. I am, by their standards, a lapsed engineer who ran away to join the circus as one of its lesser clowns. Terkowitz's memo emphasizes customer outcomes and engineering judgement, two things I would absolutely not delegate to AI any time soon. (Note: I am writing this in October of 2026, with the full understanding that previous comments on the capabilities where AI falls short tend to age like fine milk.)
（注：我写下这些时是 2026 年 10 月，充分理解之前关于 AI 短板的评论往往像牛奶一样，放久了只会变质。）它记录了（当下）AI 工具无法改进的工作。这比假设所有对 AI 的反对天然来自担心被取代、利己的“卢德分子”要好得多。它在衡量方面也说了句聪明话：看 AI 采用率第 90 百分位的团队，也就是消耗 token 最多的那些团队，检查他们的交付成果是否相应提升了。这很棒！大声疾呼吧；我们都应该这么做。
It documents work that (today) AI tools aren't improving. That's way better than assuming that every objection to AI inherently comes from some self-interested Luddite who's scared of being replaced. It also says something smart about measurement: look at the 90th percentile of AI adoption, at those teams burning the most tokens, and check whether their delivery actually went up commensurately. This is great! Shout it from the rooftops; we should all be doing such things.
但我仍存疑虑。备忘录说：“如果你的工作无法从当前的 AI 工具中受益，那是一个发现，而非过失。”记录下来，拿给经理，共同解决问题。我对这句话里的每一个字都赞同！问题是，引用这句话的晋升材料能不能过关。
But still, I wonder. The memo says “If your work does not benefit from current AI tooling, that is a finding, not a failing.”Document it, bring it to your manager, work through the problem. I agree with every word of that! The question is whether anyone's promo doc is gonna survive citing it.
接下来会发生什么。备忘录承认投入指标“存在深刻缺陷”，但下一段却说还是要小心地用。接着又警告不采用 AI 的人正在落后。这三句话表达了三种不同立场，彼此完全不一致。这不是糊涂；我认为这是在找借口。
Here's what happens next. The memo concedes that input metrics are "deeply flawed," but then in the next paragraph says to go ahead and use them anyway, carefully. It then warns that non-adopters are falling behind. Those are three different positions within three sentences and they're not at all aligned with one another. That's not muddled; I think it's cover.
经理可以引用“这是一项发现，而非缺陷”，来解释一位强项工程师为何跳过 AI 工具；等到要把某人列入绩效改进计划（PIP）时，又可以引用“落后于人”。这两种说法都符合既定政策；具体采用哪种解释，全凭经理在特定情境下自行决定。
A manager can cite "a finding, not a failing" when a strong engineer skips the AI tool, and then cite "falling behind" when it's time to PIP someone. Both are congruent with their stated policy; you get to decide which interpretation you want to go with in a given situation.
经理将如何处理合理的不使用 AI 情况？晋升和绩效决策是否以奖励这些长期成果的方式制定？还是说他们走起了捷径、钻起了空子，只为优化那些低成本易衡量的指标，奖励工具使用活跃度？因为只要给我一个指标，我就会把它变成目标。绝大多数员工也会如此。一旦发生这种情况，人人都会受损 —— KiroRank 的诞生正是如此。大家都在兜售 Token —— 亚马逊也不例外。
How will managers handle justified AI non-use? Are promotion and performance decisions being made in a way that rewards these long term outcomes? Or are they instead taking the easy weasel way out, optimizing for what's cheap to measure, and rewarding tool activity? Because if you give me a metric, I will turn it into a target. So will an overwhelming majority of employees. When that happens, everyone loses — it's how KiroRank happened in the first place. Everyone's selling tokens — including Amazon I write this after two days of attending GitHub Universe, where they talked about how agents start roughly 40% of PRs now.
我在参加完 GitHub Universe 两天后写下此文，会上他们提到，现在大约 40% 的拉取请求（PR）由智能体发起。然而，Jay Parikh 在主题演讲中的论点是，有用的产出不是“更多代码”，而是完成的成果：交付的功能、修复的漏洞、解决的安全问题、让喧哗的专栏作家闭嘴等等。问题在于，他们的整个商业模式与此背道而驰；他们采用按消费计费的模式向客户收费，而非按产出计费。目前，没有任何机制将“AI 支出”与“值得付出努力的产出”挂钩。
And yet, Jay Parikh’s keynote argument was that useful output wasn't "more code," but rather completed outcomes: features shipped, bugs fixed, security issues addressed, loudmouth columnists silenced, etc. The problem here is that their entire business model cuts against that; they're billing in a model that charges customers on a consumption basis, not an output basis. There's nothing, today, that ties "AI spend" to "output that was worth the effort."
这又把话题拉回到亚马逊身上。备忘录称，Token 最大化与节俭背道而驰，对亚马逊的内部成本支出而言，确实如此。与此同时，AWS 却按 Token 向 Bedrock 和 Kiro 客户收费。公司内部，Token 最大化是要杜绝的问题；公司外部，它却是营收计划。®
Which brings us back to Amazon. The memo says tokenmaxxing is at odds with frugality, and for Amazon’s internal cost line, it is. Meanwhile AWS bills Bedrock and Kiro customers by the token. Inside the building, tokenmaxxing is a problem to be stamped out. Outside it, it’s the revenue plan. ®