BUILDERS · 2026-06-22 · 多模型自动路由与 Agent 编排层正在成为下一代应用的基础设施。

今天读这三行就够

多模型自动路由与 Agent 编排层正在成为下一代应用的基础设施。

高质量上下文管理与知识库建设取代提示词工程，成为产出可靠结果的核心。

智能体将深度接管现有软件工作流，安全护栏、数据溯源与代码驱动交互成为关键设计要素。

大家在聊什么

Agent 路由与编排层崛起 — ×3 人 · 播客 · 🔥升温

行业正从单模型调用转向多模型自动路由与编排，编码智能体被验证为通用 Agent 基座，单一 API 背后的路由层将产生巨大价值。

Training Data：Google DeepMind's Logan Kilpatrick: Why the Model Eats the Harness

Aaron Levie (@levie)：Another new idea to push the state of AI architectures forward. Sakana released a model that effectively uses a mixture of models to get work done. You get a single API but then the work gets farmed out the model that best performs the task. “Fugu manages model selection, delegation, verification, and synthesis automatically. It solves tasks directly when that is enough, or coordinates a team of expert models when a problem calls for more. The complexity of a multi-agent system never reaches your code.” This is generally how applied AI products are building their agent harnesses at this point,

Peter Steinberger (@steipete)：I was skeptical about the multi-model routing. Seems my hinch was right. https://t.co/oVUUqBYRyy

上下文工程与高质量输入标准 — ×3 人 · 🔥升温

随着模型能力跃升，竞争焦点从提示词转向上下文管理；构建个人与企业知识库是解锁智能的关键，且高质量输出往往需要比输出长数倍的密集上下文作为输入。

Garry Tan (@garrytan)：I think one underestimated thing when we look back on it was how useful it is to have your own personal brain and company brain in 2026 at the dawn of usable AGI AGI gives you the intelligence You still have to collect your personal context to get the real unlock

Zara Zhang (@zarazhangrui)：I’m talking about context, not prompt

Zara Zhang (@zarazhangrui)：A good rule of thumb for preventing AI slop (in writing, design, etc): Is your input (the context) longer than the output? I've found that for the AI to produce quality results, my input is often 3-5 times the length of the output. If your input is much shorter than the output, it's almost certainly going to produce slop

Agent 消费软件的范式转移与护栏需求 — ×3 人 · 🔥升温

智能体对现有软件的调用量将呈百倍增长，这要求产品提供权威数据源、审计日志与安全护栏；同时，代码（如 HTML）正成为弥补 Agent 视觉短板、实现复杂交互的底层语言。

Aaron Levie (@levie)：Agents will use software 100X more than people. When that happens, theres a huge need for guardrails on what the agents are doing so they don’t leak data or change the wrong information, authoritative sources of truth for them to work with, logging and auditing of what they’re doing, the ability to collaborate with people through these systems, and more. A simple query on any given agentic task could pull in more data than a user touches in a month. As a result, there are lots of categories of software that when it goes headless that the usage and value go up substantially. Agents will end up

Guillermo Rauch (@rauchg)：Coding agents will squeeze every ounce of IKEA effect out of you, if you let them.

Peter Yang (@petergyang)：Why HTML turned out to be the foundation for agentic video making from @liu8in: “We’ve been trying to build a video agent. However, we learned the hard way that agents have no visual intelligence. So that’s when we turned to code. HTML is the LLM’s native language. LLMs can express not only information, but also visual aesthetics through HTML, CSS, and JavaScript. Footage, images, assets, SVGs can all sit on top of HTML." 📌 As an example, see how you can make a product video from any website URL here: https://t.co/Q2p8XzCfc6

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