Martin Fowler(@martinfowler)

NEW POST LLMs generate code incredibly fast, but to ensure they generate exactly what is intended, ...

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TL;DR · AI 摘要

DSL和良好抽象能显著提升LLM代码生成的可靠性和可审查性，Martin Fowler推荐该实践。

核心要点

  • DSL为LLM代码生成提供明确边界，降低意外输出风险
  • Unmesh Joshi通过抽象层实现LLM生成代码的可审查性
  • 领域特定语言可使LLM输出符合特定业务规则

结构提纲

按章节快速跳转。

  1. §引言

    LLM代码生成速度虽快但存在输出不可控风险

  2. ·DSL的作用

    领域特定语言通过语法约束确保生成代码符合预期

  3. ›抽象层设计

    抽象层将业务规则转化为LLM可理解的约束条件

  4. ·实践案例

    Unmesh Joshi通过DSL实现代码生成的可审查性验证

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）
  • DSL与LLM代码生成
    • 核心价值
      • 提升可靠性
      • 增强可审查性
    • 实现方式
      • 领域特定语言
      • 抽象层设计

金句 / Highlights

值得收藏与分享的关键句。

#LLM#DSL#代码生成#软件工程
打开原文

Martin Fowler on X: "NEW POST LLMs generate code incredibly fast, but to ensure they generate exactly what is intended, they need clear boundaries. @unmeshjoshi shares his experience using abstractions and Domain-Specific Languages (DSLs) to provide a strong harness. https://t.co/AIn45L4m5I" / X

Martin Fowler

@martinfowler

NEW POST LLMs generate code incredibly fast, but to ensure they generate exactly what is intended, they need clear boundaries.

@

unmeshjoshi

shares his experience using abstractions and Domain-Specific Languages (DSLs) to provide a strong harness.

martinfowler.com

DSLs Enable Reliable Use of LLMs

Why Domain-Specific Languages and good abstractions make LLM code generation reliable and reviewable.

1:30 PM · Jul 14, 2026

78.6K

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