“上下文工程”的概念正作为开发高级LLM应用比提示工程更关键的技能而出现。这种方法侧重于设计LLM交互的整个信息环境，而不仅仅是制作特定的提示。关键技术包括在上下文窗口中战略性地定位信息、仅检索最相关的数据以及实施上下文缓存以提高成本效益和效率。 AI
影响 上下文工程正成为构建可靠LLM代理的关键，侧重于数据架构和信息检索而非提示优化。
排序理由 该集群讨论了LLM开发技能的概念性转变，引用了专家意见和新兴实践，而不是特定的产品发布或研究发现。
AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →
<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://medium.com/@chinmayeejakate/context-is-an-engineering-skill-fccbff9e458f?source=rss------claude-5"><img src="https://cdn-images-1.medium.com/max/900/1*rgkUBx8Ad12M9-bR6ktFfQ.png" width="900" /></a></p><p …
<p>If you've been calling yourself a "prompt engineer" for the past two years, it's time to update your vocabulary — and your mental model.</p> <p>In 2026, the real leverage when building LLM-powered systems isn't in crafting the perfect sentence. It's in <strong>context engineer…
<h1> Prompt Engineering Is Table Stakes. Context Engineering Is the Next Frontier. </h1> <p>Salesforce published something last week that I've been thinking about: they're drawing a distinction between prompt engineering (optimizing the question) and context engineering (optimizi…