2026年10月29日 - 链接博客
如何打造出世界上最强AI-Pilled公司。 别被"闪闪发光"头条所拖延，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，探索了代理工程与前沿模型相比可能存在的流血边缘。
Spawn是一个巨大的多人游戏游戏环境，玩家可以使用提示(到游戏中的agent,Savi)来修改游戏世界。
我用手机打了几分钟，并能够促使一个城堡存在，然后是一头龙，然后骑着龙飞去那个城堡。
据Jacob说，Spawn现在由一个有线电源的集群自主开发，每月耗资超过300万令牌：
我们的"agents"将活代码直接更改，并飞船改为每小时出产，因此他们读取了每一个出错，错误报告并测量自己。 大约60%的作品起源于生产出错，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。
萨维文件自有问题当用户达到 1，或产品中Savi 达到 1时，她会归档。 它直接到agent，决定它是否是一个真正的bug来修复，我们不会修复的东西，或者需要决策的有意设计。 通常它会变成一个变化，在一小时内送达给该用户，同时在同一聊天中发一个消息。
这是持续部署，达到11:
这么紧的圈子只有在它不停止的情况下才有效所以我们把一个小时没有一艘飞船当作SEV -0 未发货的变化堆积而成，生产中已经存在的每一个问题都会持续更久。 反馈也慢了下来。 agent只能保持头部几个小时的工作，因此运输速度快于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，确切的说就是它断了的地方，没有其它地方。 当一个监视器或一个日志警报起火时，它开始或唤醒拥有事件的agent，我们故意打破一些东西来测试这些恢复路径是否起作用。
我的眉毛至少读了十几次融资我很难想象这种软件开发的风格当事情出错时
Jacob 称，第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应用安全审查中的修正时，一切停止工作：
每一个功能都被禁用，并标出一旦安全措施完成后将再次打开。 阿斯特拉通过关闭我们整个产品使不安全的东西安全。
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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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:
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 thing. 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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