Jerry Liu(@jerryjliu0)

From playing around with /goal It feels like there's less and less of a need to build any type of ...

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TL;DR · AI 摘要

文章指出，随着模型智能的发展，手动构建工作流的需求减少，目标驱动的自动化流程成为趋势。

核心要点

  • 目标驱动的自动化流程正在取代传统的工作流构建方式。
  • 模型智能能够自动推导出完成任务的底层步骤。
  • 非前沿实验室正在优化目标和评估工程，而非仅关注提示工程。

结构提纲

按章节快速跳转。

  1. §引言

    文章讨论了模型智能对工作流构建方式的影响。

  2. ·目标驱动的自动化流程

    模型智能可以自动推导任务的底层步骤，减少手动构建工作流的需求。

  3. ›非前沿实验室的优化方向

    非前沿实验室正在优化目标和评估工程，而非仅关注提示工程。

思维导图

用一张图看清主题之间的关系。

查看大纲文本（无障碍 / 无 JS 友好）
  • 目标驱动的自动化流程
    • 模型智能推导底层步骤
    • 非前沿实验室优化方向
      • 目标和评估工程

金句 / Highlights

值得收藏与分享的关键句。

#AI#自动化#模型优化
打开原文

Jerry Liu on X: "From playing around with /goal It feels like there's less and less of a need to build any type of workflow manually (whether through code, drag and drop, or a prompt). Instead, specify the goal, let the model intelligence figure out the underlying steps. If the task is" / X

Jerry Liu

@jerryjliu0

From playing around with /goal It feels like there's less and less of a need to build any type of workflow manually (whether through code, drag and drop, or a prompt). Instead, specify the goal, let the model intelligence figure out the underlying steps. If the task is repeatable, then you can gather a dataset with ground-truth, and hillclimb it for increased cost / lower accuracy. To some extent this is what every non-frontier lab is optimizing for. The world is moving from prompt engineering -> goal and eval engineering.

4:38 PM · Jun 27, 2026

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