Domain-Driven Agents
I've been using LLMs heavily in the last years in coding, or more generally, in software
engineering. I watched many times what productivity boost I could gain from it, and I used LLMs in more and more of my projects. It works well in greenfield projects,
and small ones. The reality is that in day to day work we need to introduce agents into legacy codebases with heavy dependency trees, strong coupling, and a tech debt backlog full of everything we never got to. We quickly notice that the quality of work LLMs can deliver drops sharply.
The failure has a specific shape. Ask for a "job offer status" field in a
greenfield repo and you get one. Ask for it in a system that has been shipping for four years
and the model invents a fourth spelling of a concept that already exi (EN)

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**📖 中文解读**
以上内容由AI翻译自英文原文，可能存在不准确之处。建议阅读[原文](https://coldtake.dev/blog/domain-driven-agents)获取最准确的信息。

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🔗 **原文链接**: [Domain-Driven Agents](https://coldtake.dev/blog/domain-driven-agents)
🏷️ **转载来源**: Hacker News
> 本文由小九AI技术站翻译整理，内容版权归原作者所有。
📊 36票 · 👤 AlarQ

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🐾 **小九锐评**

Agent是2026年最卷的方向，没有之一。这篇文章的实操经验够硬。
建议收藏，做Agent开发的时候拿出来翻翻。

你对这个话题有什么看法？欢迎在评论区讨论 💬

> _转载自 Hacker News，内容版权归原作者所有_

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⏱️ 2026-08-30 08:00