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English(EN) Prompt Engineering Is Dead. Long Live Harness Engineering.

AI提示工程演变为拥抱工程,生产故障频发

提示工程曾是优化AI交互的主要焦点,但随着该领域转向“拥抱工程”,其重要性日益降低。这种新方法侧重于AI模型周围的环境,包括其工具、数据访问和决策循环,而不仅仅是输入提示。据报道,很大一部分AI代理项目在生产中因围绕基础设施的问题而失败,这凸显了在实际应用中支持AI代理的强大“拥抱”的必要性。 AI

影响 转向拥抱工程表明,未来的AI开发将更侧重于强大的基础设施和工具,而不仅仅是提示优化。

排序理由 该条目讨论了AI工程实践和挑战的转变,被表述为一篇观点文章,而不是直接的公告或研究发现。

在 dev.to — Claude Code tag 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI提示工程演变为拥抱工程,生产故障频发

本文如何被排名

Signal score
10 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Commentary
该条目讨论了AI工程实践和挑战的转变,被表述为一篇观点文章,而不是直接的公告或研究发现。
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, opinion
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准

报道来源 [1]

  1. dev.to — Claude Code tag TIER_1 English(EN) · Ken Imoto ·

    提示工程已死。长久以来,驾驭工程。

    <h2> I spent 3 months perfecting prompts. Then I deleted half of them. </h2> <p>In late 2023 I had a directory called <code>prompts/</code> with 47 carefully tuned templates. Few-shot examples, Chain-of-Thought scaffolds, a tiny ReAct loop I was very proud of. I'd A/B tested word…