为智能编程代理重新设计代码规范，提升机器理解效率。
Beyond Human-Readable: Rethinking Software Engineering Conventions for the Agentic Development Era
- 提出语义密度优化原则，去除无信息冗余符号
- 压缩代码反增成本67%，因加重模型推理负担
- 支持代理导航的程序骨架设计，适配自动化开发
六十年来，软件工程规范始终以人类开发者为中心。随着基于大模型的智能体自主读写、导航和调试代码库，新的核心用户——智能代理——带来了根本不同的约束。本文系统分析了人类中心惯例在代理压力下的表现，提出关键设计原则：语义密度优化，即消除零信息内容的标记，保留高语义价值的标记。通过在四种条件（可读、结构化、压缩、工具辅助压缩）下对日志格式标记经济性的控制实验，发现反直觉结果：尽管输入标记减少17%，但激进压缩使总会话成本上升67%，因为将解读负担转移至模型推理阶段。论文进一步将该原则扩展至恢复经典反模式、提出适用于代理代码导航的程序骨架概念，并主张从根本上解耦语义意图与人类可读表达。
原文摘要 · Abstract (English)
For six decades, software engineering principles have been optimized for a single consumer: the human developer. The rise of agentic AI development, where LLM-based agents autonomously read, write, navigate, and debug codebases, introduces a new primary consumer with fundamentally different constraints. This paper presents a systematic analysis of human-centric conventions under agentic pressure and proposes a key design principle: semantic density optimization, eliminating tokens that carry zero information while preserving tokens that carry high semantic value. We validate this principle through a controlled experiment on log format token economy across four conditions (human-readable, structured, compressed, and tool-assisted compressed), demonstrating a counterintuitive finding: aggressive compression increased total session cost by 67% despite reducing input tokens by 17%, because it shifted interpretive burden to the model's reasoning phase. We extend this principle to propose the rehabilitation of classical anti-patterns, introduce the program skeleton concept for agentic code navigation, and argue for a fundamental decoupling of semantic intent from human-readable representation.
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