🧠 How AI Agents Will Redesign the Web

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In today’s Sunday Special:

• 📜The Prelude

• 📱New Users Require New Interfaces

• ⚙️Core Components of Agent-First Web Design

• 🔑Key Takeaway

Read Time: 6 minutes

🎓Key Terms

• AI Agents: Virtual employees who can autonomously plan, execute, and refine their actions.

• HyperText Markup Language (HTML): The language used to structure and display content on websites.

• Application Programming Interface (API): Allows multiple software applications to share data, features, and functionality back and forth with each other.

• Retrieval-Augmented Generation (RAG): Improves the accuracy of advanced AI models by retrieving relevant, up-to-date data directly related to a user’s query.

🩺 PULSE CHECK

📜THE PRELUDE

AI Agents are beginning to change how we interact with the Internet by acting on our behalf. They can autonomously operate across websites to browse, book, and buy without us lifting a finger.

While humans navigate websites visually, AI Agents navigate them structurally. In other words, we read pixels while they read code.

The digital world has been optimized for humans. Now, it’ll have to be restructured to support Agentic AI. So, how exactly do AI Agents work? How will digital infrastructure adapt to accommodate them?

📱NEW USERS REQUIRE NEW INTERFACES

What Exactly Are AI Agents?

Unlike rule-based programs, like a Spam Filter that relies on a predefined set of rules to classify incoming emails as either “Spam” or “Not Spam,” AI Agents autonomously analyze digital environments to plan, execute, and adapt in real-time.

In Cognitive Psychology, which examines how people think, learn, and remember, perception occurs when people take in information through their senses. For example, feeling the texture of a fabric or smelling a freshly baked pie. Similarly, AI Agents develop a perception of a user’s query by processing various forms of data across several sources (e.g., text, image, audio, video, or code).

For example, when planning a trip, an AI Agent might coordinate across multiple APIs: utilize reviews through a Tripadvisor API to suggest highly-rated hotels, leverage a Google Maps API to determine the most efficient transportation methods, and check an OpenTable API to find the best restaurants.

Think of all the ways we use the Internet. AI Agents will cover all those use cases and others we can’t foresee. But today’s Internet isn’t configured to support Agentic AI. Fortunately, we can learn from the last overhaul of Internet Infrastructure.

Lessons From the Mobile Revolution?

When Apple’s iPhone 2G was released on June 29th, 2007, it transformed the world. Eventually, mobile website traffic surged, prompting companies to adapt by creating mobile websites that crammed desktop experiences into smaller screens. These early solutions were functional but failed to harness the full potential of mobile devices. It took nearly a decade of innovation to develop mobile-friendly websites with fewer pop-ups and a new User Interface (UI). Navigational menus became collapsible “hamburger icons” to save screen space with “pinch-to-zoom,” “pull-to-refresh,” and “swipe-to-advance” commands.

Now, we face a similar inflection point with AI Agents. Much like Apple’s iPhone 2G kickstarted “mobile-responsive designs,” AI Agents will lead to “agent-responsive designs” that require a complete rethinking of how websites, authentication mechanisms, and a business’s sensitive data are structured and accessed.

⚙️CORE COMPONENTS OF AGENT-FIRST WEB DESIGN

Websites designed for AI Agents will prioritize MAchine-Readable Formats (MARF) over visually optimized UIs. Agentic AI-friendly websites will include four core components:

1. Transparent Document Object Model (DOM): The DOM is a webpage’s blueprint, which defines HTML elements like text and images within structured code. Humans gather information by viewing UIs, whereas AI Agents read structured code. When websites use messy, hidden, or overly complex code, AI Agents struggle to extract relevant information. For example, a shopping website designed for humans might bury a product’s price deep within a programming script. In contrast, An Agentic AI-friendly shopping website would use a straightforward HTML span tag like <span class= “price”>$19.99</span> within a structured code layout, enabling AI Agents to quickly find and compare a product’s prices without relying on additional computational resources.

2. Metadata and Accessible Rich Internet Applications (ARIA): Both Metadata and ARIA Labels are invisible to humans but critical to AI Agents. Metadata provides critical context about a website’s content. For example, when an AI Agent summarizes today’s top business news, it doesn’t read headlines visually. Instead, it filters articles based on Metadata like <meta name= “section” content= “Business”> and <meta name= “date” content= “2025-04-06”> to quickly locate relevant business news. ARIA Labels are unique HTML attributes that describe the purpose of a website’s interactive elements like buttons. A human may recognize a shopping cart icon visually, but an AI Agent needs an explicit HTML attribute like <aria-label= “Add to Cart”> to understand the button’s purpose.

3. Direct Knowledge Base (KB) Access: When AI Agents gather information from websites, they often rely on Web Scraping. But frequent website updates make Web Scraping less reliable. In response to this issue, businesses offer APIs, which allow AI Agents to request structured data directly from a business’s databases. While API access is often restricted due to security concerns, AI Agents will encourage a shift towards more regulated API access. When accessing APIs, AI Agents will use RAG to retrieve specific information without needing to sift through multiple sections of a business’s databases. For example, an AI Agent designed for booking hotels will directly access a hotel’s API and use RAG to locate internal documents for policies on late check-outs; if the information isn’t published, the AI Agent might activate a Voice Agent to call the receptionist.

4. Streamlined Authentication: When you log in to any website (e.g., Chase Bank) using your Google account, Google’s Open Authorization (OAuth) protocol enables you to set up a secure authentication process without sharing your password with that website. For example, Chase Bank redirects you to Google’s OAuth protocol, where you log in and consent to share your Google account information with Chase Bank, including your Google username and Gmail email address. Then, Google issues an authorization code, and Chase Bank exchanges it for an OAuth Access Token, allowing Chase Bank to securely access your Google account without seeing your password. Similarly, Google will provide AI Agents with an OAuth Access Token to log in on your behalf to perform complex multi-step tasks. For example, an AI Agent tasked with managing your monthly monetary budget might need to examine your credit card purchases every week through Chase Bank.

🔑KEY TAKEAWAY

AI Agents can autonomously navigate websites and complete complex multi-step workflows. But the Internet isn’t built for them yet. Unlike humans, AI Agents don’t view interfaces; they interpret code. Today’s websites prioritize visuals over underlying code, making it harder for AI Agents to function effectively. Until websites adapt to AI Agents, today’s underlying code formats of webpages will limit Agentic AI adoption.

📒FINAL NOTE

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