一位Anthropic的工程师展示了一种与Opus等大型语言模型交互的新颖方法，他建议用户不应直接提示，而应构建能够自我提示的系统。这种方法允许更复杂的代理行为，使AI能够记住过去的交互、自我纠正错误并随着时间的推移持续改进其性能。 AI
影响 提出了一种与LLM交互的新范式，可能实现更自主、更强大的AI代理。
排序理由 来自一位工程师关于与LLM交互方法的观点文章，而非直接发布或产品公告。
AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →
Anthropic工程师提出Opus的自提示系统
本文如何被排名
- Signal score
- 8 / 100
- Composite score across the factors below. Higher = stronger signal that this story matters right now.
- Newsworthiness bucket
- Commentary
- 来自一位工程师关于与LLM交互方法的观点文章，而非直接发布或产品公告。
- 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]
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你不应该提示 Opus。你应该构建一个能自行提示的系统。
<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://iamdgarcia.medium.com/youre-not-supposed-to-prompt-opus-you-re-supposed-to-build-a-system-that-prompts-itself-8d6ebbf3a551?source=rss------claude-5"><img src="https://cdn-images-1.medium.com/max/1983/0*sF…