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AI Agent Workflow Collaborating with Fable 5 and Codex

AI Agent Workflow Collaborating with Fable 5 and Codex

 宝玉

@dotey

现在我很多复杂一点的任务都是 Fable 5 写方案，Codex 去执行，Fable 5 验收，相对来说可以做出比较靠谱的方案，以及兼顾性价比。具体是这么做的：

• Fable 5 的产出是技术方案文档（图1）

一方面文档方便批注修改，另一方面文档方便其他 Agent 快速上手

• 文档确认后在当前先 /compact 一次

这一步不是必要的，但是有好处，因为后续还要在同一会话去验证，/compact 压缩后，节约后续的上下文空间，之所以讨论方案就马上发送 /compact，因为这时候 Prompt Caching 还在，成本低，后面缓存过期了 compact 要贵一点。

• 把文档交给 Codex （GPT-5.6 Sol xhigh）去执行（图2）

如果任务明显比较复杂，我一般会加上 /goal，这样中间就不需要反复去 continue，一次性把任务完成

• Codex 完成后让 Fable 验证（图3）

直接告诉 Fable 其他 Agent 已经实施了，让它确认有没有遗漏，或者方向有无偏离。

如果有些遗漏之类的，把 Fable 的反馈发回给 Codex（图4），不需要新开会话，在同一个 Codex 会话，Codex 会根据反馈继续完善。

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如果用 Opus 5 替代 GPT 5.6 也可以，做法上可以跟上面一样新开会话，用文档传递上下文。

也可以直接让 Fable 5 开 SubAgent 并指定用 Opus 5 模型，并且要求在 SubAgent 完成任务后验证。

但是我执行下来 Opus 5 不如 GPT 5.6 Sol 稳定，也不如 GPT 5.6 Token 耐用，所以宁愿麻烦一点。Show More

!Image 3: 媒体 1

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Aug 3, 2026, 7:32 PM View on X

27 Replies

23 Retweets

142 Likes

11.8K Views  宝玉 @dotey

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One Sentence Summary

The author details a multi-Agent collaboration workflow where Fable 5 handles proposal writing and verification, while Codex (GPT-5.6 Sol) handles execution, balancing solution quality and cost-effectiveness.

Summary

Baoyu shares his actual practice in complex tasks: first, Fable 5 generates a technical solution document, making it easy to annotate and for other Agents to get up to speed quickly; after document confirmation, he runs /compact to compress context to reduce subsequent costs; then he hands the document to Codex (GPT-5.6 Sol xhigh) for execution, adding /goal when needed to complete the task in one go; after completion, he lets Fable verify and iteratively improve based on feedback within the same Codex session; he also mentions that Opus 5 can be used as a replacement but is less stable and cost‑efficient than GPT-5.6 Sol. The post includes four operation screenshots, steps are clear and highly actionable.

AI Screening

88

Influence Score 64

Published Today

Language

Chinese

Tags

Fable 5

Codex

AI Agent Workflow

Multi-Agent Collaboration

Prompt Engineering

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