Prime Agent: A self-improving RLM agent
Today, we are launching
Prime Agent
, our self-improving coding harness designed around two abstractions, the
Recursive Language Model (RLM)
[
citation
] and
Continual Harness
[
citation
]. Modern harness designs were built around the capabilities of earlier generations of models, and they do not reflect what frontier models can do today: fixed tool-calling schemas and context compaction force the model to work around its own scaffolding instead of leveraging it. Static, hand-engineered sub-agents, prompts, skills, and memory are set once at design time and never adapt to what the agent learns while running. We believe that harnesses should instead extrapolate on current model capabilities toward the next frontier of reasoning patterns.
Prime Agent i (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://www.primeintellect.ai/blog/prime-agent)获取最准确的信息。

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🔗 **原文链接**: [Prime Agent: A self-improving RLM agent](https://www.primeintellect.ai/blog/prime-agent)
🏷️ **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。
📊 71票 · 👤 Xeophon

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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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⏱️ 2026-08-06 08:01