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Simon Willison更新于 10月30日 14:42

Simon Willison 转述 Spawn 如何用 Fable 模型智能体集群自主开发游戏

Building a multiplayer game world with autonomous Fable-class models

AI 导读

Simon Willison 推荐 Jacob Sansbury 的文章,介绍多人游戏环境 Spawn 由 Fable 驱动的智能体集群自主开发,每月 token 成本超过 300 万美元。文中称智能体直接修改线上代码并每小时发布,约 60% 的工作源自生产错误、Savi 提交的 bug 报告或功能请求,一小时未发布被视为最高级别事故。Jacob 表示 Fable 5 及 5.1 才让这种自主程度成为可能,Opus 5.5 难以胜任,而用 GPT-6 Astra 处理安全审查修复时,它把不安全的功能全部关闭,导致一切停摆。

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文章记录了一家游戏公司用智能体集群自主改代码、每小时上线的做法,以及不同前沿模型在其中的实际表现差异。

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#smallhead

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.

Posted 29th October 2026 at 5 pm

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This is a link post by Simon Willison, posted on 29th October 2026.

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Simon Willison