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| Main Author: | |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.07502 |
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| _version_ | 1866910113843904512 |
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| author | Ustynov, Dmytro |
| author_facet | Ustynov, Dmytro |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_07502 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Beyond Human-Readable: Rethinking Software Engineering Conventions for the Agentic Development Era Ustynov, Dmytro Software Engineering Artificial Intelligence 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. |
| title | Beyond Human-Readable: Rethinking Software Engineering Conventions for the Agentic Development Era |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2604.07502 |