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arXiv 提交日期: 2026-04-23
📄 Abstract - Agentic AI-assisted coding offers a unique opportunity to instill epistemic grounding during software development

The capabilities of AI-assisted coding are progressing at breakneck speed. Chat-based vibe coding has evolved into fully fledged AI-assisted, agentic software development using agent scaffolds where the human developer creates a plan that agentic AIs implement. One current trend is utilizing documents beyond this plan document, such as project and method-scoped documents. Here we propose this http URL, a community-governed, field-scoped epistemic grounding document, using mass spectrometry-based proteomics as an example. This explicit field-scoped grounding document encodes Hard Constraints (non-negotiable validity invariants empirically required for scientific correctness) and Convention Parameters (community-agreed defaults) that override all other contexts to enforce validity, regardless of what the user prompts. In practice, this will empower a non-domain expert to generate code, tools, and software that have best practices baked in at the ground level, providing confidence to the software developer but also to those reviewing or using the final product. Undoubtedly it is easier to have agentic AIs adhere to guidelines than humans, and this opportunity allows for organizations to develop epistemic grounding documents in such a way as to keep domain experts in the loop in a future of democratized generation of bespoke software solutions.

顶级标签: agents llm machine learning
详细标签: ai-assisted coding epistemic grounding agent scaffolds software development proteomics 或 搜索:

智能体AI辅助编程:在软件开发中植入知识根基的独特机遇 / Agentic AI-assisted coding offers a unique opportunity to instill epistemic grounding during software development


1️⃣ 一句话总结

本文提出通过创建由社区维护的领域知识文档(以质谱蛋白质组学为例),让智能体AI在辅助编程时自动遵循学科硬约束和行业惯例,从而让非专业用户也能生成科学正确、符合最佳实践的软件,并为未来定制化软件的民主化开发提供了保障。

源自 arXiv: 2604.21744