2026年10月29日 - 链接博客
如何打造"世界最AI-Pilled公司". 别被"闪闪发光"头条所耽误，雅各布·桑斯伯里描述他们如何建造"Spawn"的这篇作品，是一个令人着迷的探索，探究了代理工程与前沿模型之间可能存在的流血边缘。
Spawn是一个巨大的多人游戏环境，玩家可以使用提示(对游戏中的agent,Savi)来修改游戏世界。
我用手机开了几分钟然后就让一座城堡存在然后是一条龙然后骑着龙飞到城堡四周
根据雅各布的说法，"Spawn"现在由一台有线电动的集群自动开发，每月耗资超过300万令牌("我们在AI令牌上花费30x工资").
我们的agents将直播代码直接更改，飞船改为小时生产，因此他们读取了每一个错误，错误报告以及测量自己。 大约60%的作品起源于制作错误，Savi bug 报告(Savi是您在 Spawn 中创建的游戏的AI)，在我们的日志中有些奇怪，或者一个特性请求。
萨维文件本身有问题当用户达到 1，或产品中的Savi 达到 1时，她会将其存档。 它直接到agent，决定它是否是一个真正的bug来修复，一些我们不会修复的东西，或者需要决定的有意设计。 通常它会变成一个变化，在1小时内送达给该用户，并在同一个聊天中带一个消息。
连续部署达到11次：
只有不停的循环才有效所以我们把一个小时没有船当SEV-0处理我们最严重的事件未发货的变化堆积起来，生产中已经存在的每一个问题都会持续更长的时间。 反馈亦缓。 agent只能让头部保持几个小时的工作，因此运输速度比这实际帮助它保持连贯。 [...]
我们可以在30秒内把一个破碎的改变倒回去，确切地说就是它破碎的地方，没有其它地方。 当一个监视器或日志警报起火时，它会启动或唤醒拥有事件的agent，我们故意打破一些东西来测试这些恢复路径是否有效。
我的眉毛融资至少读了十几次这个。 我很难想象这种软件开发的风格当事情出错时
Jacob 称认为5号线(然后是5.1)是使这种程度的自主成为可能的模式。 Opus 5.5并不完全为他们黑入，当他们尝试GPT-6 Astra应用安全审查的修复时，一切停止工作：
每一个功能都已被禁用，并标出一旦安全修复后将再次打开。 Astra已经检查了我们的全部产品并且通过关闭它们来保证安全
这些类型的极端实验，就是为什么我对游戏开发感到兴奋，作为探索今天编码的agents所能做的边缘的底物。
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本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
29th October 2026 - Link Blog
How I Built the Most AI-Pilled Company in the World. Don't be put off by the clickbait headline, this piece by Jacob Sansbury describing how they are building Spawn is a fascinating exploration of the bleeding edge of what's possible with agentic engineering against frontier models.
Spawn is a massively multiplayer gaming environment where players can use prompts (to the in-game agent, Savi) to modify the game world.
I fired it up on my phone for a few minutes and was able to prompt a castle into existence, then a dragon, then ride the dragon to fly around that castle.
By Jacob's telling, Spawn is now being developed autonomously by a swarm of Fable-powered agents costing over $3 million in tokens per month ("we spend 30x payroll on AI tokens").
Our agents change the live code directly and ship to production hourly, so they read every error, bug report and metric themselves. About 60% of our work starts from a production error, a Savi bug report (Savi is the AI you build games with in Spawn), something odd in our logs, or a feature request.
Savi files bugs herself. When a user hits one, or Savi hits one in the product, she files it. It goes straight to an agent that decides whether it's a real bug to fix, something we won't fix, or intentional design that needs a decision. Usually it becomes a change, delivered to that user within an hour, with a message in the same chat.
This is continuous deployment turned up to 11:
A loop this tight only works if it never stops, so we treat an hour without a ship as a SEV-0, our most severe kind of incident. Unshipped changes pile up, and every problem already in production lasts longer. The feedback slows down too. An agent can only keep a few hours of work in its head, so shipping faster than that actually helps it stay coherent. [...]
We can roll back a broken change in 30 seconds, exactly where it's broken and nowhere else. When a monitor or a log alert fires, it starts or wakes an agent that owns the incident, and we break things on purpose to test that those recovery paths work.
My eyebrows raised at least a dozen times reading this. I have trouble imagining this style of development working on software with higher stakes for when something goes wrong, but for a game this appears to be working surprisingly well.
Jacob says that Fable 5 (and then 5.1) was the model that made this level of autonomy possible. Opus 5.5 doesn't quite hack it for them, and when they tried GPT-6 Astra to apply fixes from a security review everything stopped working:
Every feature had been disabled and marked to be turned on again once the security fixes were done. Astra had gone through our whole product and made the insecure things secure by turning them off.
These kinds of extreme experiments are why I'm excited about game development as a substrate for exploring the edges of what today's coding agents can do.
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