English(EN) Stop Loading Your Entire Instruction System Into Every Session

LLM指令架构通过模块化设计减少令牌负载

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-17 08:00

一位开发者提出了一个用于LLM指令系统的模块化架构，以减少令牌使用并提高效率。该系统不一次性将所有指令加载到上下文中，而是使用一个精简的入口点作为路由器，仅在与当前任务相关时动态加载专门的模块。这种方法旨在通过确保只有必要的指令在上下文中处于活动状态来降低成本、减少延迟并提高信噪比。 AI

影响这种模块化方法可以通过优化上下文窗口使用，显著降低LLM应用程序的运营成本和延迟。

排序理由该项目描述了一种新颖的LLM指令系统架构方法，类似于研究提案或技术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该项目描述了一种新颖的LLM指令系统架构方法，类似于研究提案或技术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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: infra; 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: 70 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

dev.to — LLM tag TIER_1 English(EN) · Ben Witt · 2026-06-17 08:00

停止将整个指令系统加载到每个会话中

<p>Most people talk about better prompts. Hardly anyone talks about what happens before every prompt: the instructions the assistant loads into the context before the actual work begins.</p> <p>Depending on the system, you pay for that in different ways: input tokens, latency, re…