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AI 资讯

Understanding Middleware in Deep Agents (With Runnable Examples)

If you've built even a simple AI agent, you've probably noticed that the "agent loop" itself is deceptively simple: the model gets a message, decides whether to call a tool, gets the result back, and repeats until it has an answer. But real-world agents need a lot more than that bare loop to actually work well. What happens when a conversation gets so long it blows past the model's context window? What if a tool call gets interrupted halfway through and leaves your message history in a broken state? What if you want the agent to keep a running todo list of what it's working on, or delegate parts of a task to a specialized sub-agent, or read and write files as part of its job? You could bolt all of this onto your agent manually. Or, if you're using Deep Agents, you get most of it for free through something called middleware . This post walks through what middleware actually is, why Deep Agents ships with a default stack of it, and how each piece behaves, with runnable code for each one so you can see it working instead of just reading about it. So What Is Middleware, Really? If you've done any web development, the term "middleware" probably already rings a bell. It's the same idea here. Middleware is code that sits around the core agent loop and gets a chance to run before or after certain things happen, like before a tool call executes, after the model responds, or right before messages are sent to the model. Instead of writing all of this logic directly inside your agent, you attach separate, independent pieces of middleware that each handle one specific concern. This matters for two reasons: You don't have to build common behaviors from scratch. Things like managing a todo list, summarizing long conversations, or handling file access are problems almost every non-trivial agent runs into. Deep Agents ships default middleware for these so you don't reinvent them every time. You can customize behavior without touching the agent's core logic. Need a custom summarizati

2026-07-22 原文 →
AI 资讯

What on Earth is "Agentic Browsing"?

I Built a Vanilla JS Web App that Scored 100/100 Under Lighthouse’s New "Agentic Browsing" Audit. Here’s What It Means. If you have run a performance audit on PageSpeed Insights or Lighthouse recently, you might have noticed a fascinating new line item quietly slipping into the metadata report: Agentic Browsing . When I audited my free tool suite, Paktheta , I managed to hit the ultimate developer milestone— a perfect 100/100 across Performance, Accessibility, Best Practices, and SEO. But seeing that perfect score alongside the label "Agentic Browsing" got me thinking. What exactly is an AI-driven agent experiencing when it hits our sites, and why is this the new gold standard for web performance? Let's dive into what Agentic Browsing actually means for the future of optimization. What on Earth is "Agentic Browsing"? Historically, speed tests like Lighthouse were passive. A headless browser opened your URL, waited for the page to load, recorded metrics like First Contentful Paint (FCP) and Largest Contentful Paint (LCP), and closed the tab. It was a linear, predictable, and frankly synthetic snapshot. Agentic Browsing changes the paradigm entirely. Instead of a basic static script, modern auditing platforms use autonomous, intelligent browser agents. Guided by modern AI-driven browser control (using updated instances like HeadlessChromium), these agents don't just stare at your page—they explore it like a real human would. An agentic audit runner will: Identify interactive buttons and click them to test responsiveness. Scan form elements to see if they accept paste commands cleanly. Intelligently look for broken layout shifts (CLS) by dynamically scrolling and triggering micro-animations. Interact with JavaScript components to see if they block the main execution thread. In short: It simulates real, unpredictable human behavior at lightning speed. If your site relies on bloated frameworks that look fast initially but lock up the second a user tries to interact, an a

2026-06-17 原文 →
产品设计

Windows is back on the Microsoft menu

I can't remember the last time Microsoft kicked off a Build keynote with Windows front and center, but that's exactly what CEO Satya Nadella did this week. Nadella didn't address the issues Microsoft is trying to fix in Windows 11 but chose to woo the audience with Microsoft's slick Surface RTX Spark Dev Kit instead, […]

2026-06-05 原文 →
开发者

What’s next for Microsoft’s Surface PCs?

Nearly 10 years ago I reviewed my favorite Surface device. Microsoft hand-delivered its Surface Studio all-in-one PC to me, and I was hooked from the moment I switched it on. It had a beautiful floating touchscreen that you could push all the way down into a drawing board mode, making it unlike anything I had […]

2026-05-29 原文 →