In 2001, a decade after he invented the World Wide Web, Tim Berners-Lee articulated a new vision. Together with two colleagues, he published an article in the magazine Scientific American in which he outlined what he called the “Semantic Web”: an internet designed to be navigated by autonomous software agents that could address our every need, without requiring us to muck about with browsers and search engines ourselves.
To illustrate what this might look like, Berners-Lee and his colleagues told a story about a pair of siblings who use their agents to automatically research and book physical therapy appointments for their mother, making sure they would be covered by insurance and fit their busy calendars.
At the turn of the millennium, this vision seemed far-fetched: Google had only been online for a couple of years, and most people were still on dial-up connections. But a quarter-century on, the dream of autonomous software agents that use the internet and carry out tasks for us has finally been realized. New tools such as Meta’s blockbuster Muse agent, OpenAI’s Dots, and Anthropic’s are being given access to people’s email inboxes and bank accounts, Meanwhile, in a series of worrying incidents, agents created by OpenAI broke free of their sandboxes and caused havoc online.
Just as the rise of smartphones sparked the development of a more atomized and attention-grabbing internet, the advent of powerful AI systems heralds a new era: We’re facing not the semantic web but the agentic web. This new web is developing out of sight and in ways that might not be entirely within our control. As it grows, the agentic web will inevitably transform the human web—and whether the human web survives this transition is anyone’s guess.
For Berners-Lee’s original vision to work, internet users would have had to annotate the pages they built with special tags so that a software agent could understand each element’s meaning—say, “street address” for the part of a physical therapy office’s web page that indicates its location and “appointment types” for the list of services. And so the idea never really caught on. “It’s a lot of labor,” says Eni Mustafaraj, a professor of computer science at Wellesley College. “And the benefits of that were not obvious.” For the next two decades, then, the internet remained a place that put humans first, with the odd Twitter reply bot or web scraper to round things out.
Large language models changed that. Unlike the agents that Berners-Lee was imagining, today’s LLM-based agents don’t need any tags to understand which part of the text on a clinic’s site is its address and which details the services it offers. They can search for and process text far faster than any human, and agents with multimodal capabilities can even interpret screenshots of websites and click on specific elements such as hyperlinks and drop-down menus.
They’re also just a way more intuitive means of finding information and accomplishing tasks online. Rather than poring over pages of Google results to find a budget-friendly product dupe or a half-remembered meme, why not have Claude or ChatGPT peruse dozens of sites in just a few minutes, guided only by your vague query? Or go one step further and use a personal assistant agent like Muse to hunt down a restaurant reservation or book a flight.
As agents flood online spaces, this new user base is changing the web for good. Time magazine, for instance, is publishing versions of its articles that are easier for agents to parse and has started selling ads targeted at them. Companies from Etsy to Expedia have partnered with the major AI firms to build tools that allow agents to interface seamlessly with their services.
Despite these early efforts, it’s still tough to tell exactly what forms the agentic web will take and how it will change our online experience. Depending on how it’s designed and who controls access to it, we could be in for something that’s as open and customizable as the web of the early 2000s, only far easier to use. Alternatively, we could be reduced to viewing much of the web through tiny portholes controlled by a few dominant platforms, as independent sites and creators struggle to survive the shift. And as this summer’s series of OpenAI security incidents suggests, the agents might even build their own online networks and resources—whether we want them to or not.
How this plays out also depends on us: which parts of our online lives we’re happy to delegate to our agents and where we will still demand a human-centric internet. “There’s a lot we don’t know yet about how users want to use [agents],” says Ajit Varma, head of Firefox at Mozilla. But whatever does happen, the changes will be big. “It’s probably on par with getting a mobile phone,” he says. “I think things are going to change very dramatically.”
Building a web for agents
There are two ways to approach building the agentic web. The first involves training agents to use browsers like humans—scrolling, clicking, typing—and letting them loose on the web that we’re all used to. The second requires building tools that allow agents to interface with the internet via text and code, their preferred media. That possibility offers more separation between the human and the agentic web: designers can create different experiences for those who use text commands and those who use browsers.
When Siva Reddy, a professor of computer science and linguistics at McGill University, began studying LLM agents in 2024, he focused on the first option. “At that time, we thought it should be that the best agent in the world is probably an agent that can use a browser,” he says. Such an agent would integrate seamlessly with the preexisting human web, and its owner could easily supervise it by watching as it navigated familiar interfaces.
The frontier AI companies were already developing these “computer-use agents.” But they didn’t work terribly well—at least not at first. “There’s a lot of moving pieces [on the web], and they are not really optimized for automatic consumption,” says Xing Han Lu, a graduate student in Reddy’s lab at McGill. We humans are naturals at interacting with graphical interfaces using a keyboard and mouse, but agents are not.
PINGNAN LU
So Reddy and Lu pivoted toward the second, tool-based approach. In the summer of 2025, they expounded on this view in a preprint paper envisioning a new kind of web interface that would allow agents to interact with websites just as effectively as we do. Such a full-featured version of the agentic web doesn’t yet exist, but it is emerging in smaller ways. For example, if you open up Claude, ChatGPT, or Muse, you’ll find an option to add a wide variety of “plug-ins” or “connectors” that your agents can use: Gmail connectors allow your agent to triage your inbox, and Instacart plug-ins let your agent do your grocery shopping. Under the hood, these plug-ins allow your agent to interact with the back ends of websites using text commands. When human engineers design these plug-ins, they can decide how they want to allow agents to interact with the website—and what they don’t want to let them do.
In this way, connectors can help make agents much safer online. For instance, Muse can buy products for you using its connector with Stripe’s Link payment service. Stripe knows your credit card number, but the agent doesn’t see it, and the connector requires human confirmation before a purchase goes through—so Muse can’t go on an unlicensed shopping spree.
Agents also use specialized tools to find information online. They don’t type questions directly into the Google search bar; in fact, they often don’t even access the websites they reference. Instead, they query text databases collected by simple search crawler bots. People who want to make web content specifically for agents can take advantage of these crawlers: Time has pioneered that approach by serving its agent-oriented ads to crawlers in the hopes that they will be incorporated into these databases and surface when agents search for information.
But in recent months, an alternative to this bespoke tool approach has finally started to seem viable. The major AI companies have managed to train much more successful computer-use agents than were previously available. GPT-6 Astra, which OpenAI released last September, achieved a 73% success rate on OSWorld 2.0, a benchmark that tests computer-use agents on their ability to complete complex, multistep tasks using software such as Slack and Salesforce.
Such results indicate that agents are close to being able to navigate the human web just as readily as we can. “We thought we had to build a bridge to the AI agents, [but] the AI agents just were able to cross the bridge already,” says Ethan Mollick, a professor at the Wharton School at the University of Pennsylvania. “The agentic web is here earlier than people expected.”
This version of the agentic web, though, is much trickier for us to steer. If you want to make a capability or piece of information available to humans who browse your website, you need to accept that it will also be available to agents—unless you want to block agents entirely, which could come with its own costs.
As agents come to account for a larger portion of traffic on our formerly human-dominated web, designers will undoubtedly start to consider an agentic as well as a human audience. But according to Mollick, we still don’t have much sense of how to design web content for agents. He’s experienced this firsthand: When he was building a web page for his new book, Co-Existence, he decided to put together an agent-directed version that tells agents why they might want to recommend the book to their users. When newer models see the site, Mollick says, they don’t recommend the book; instead, they comment that the website seems to be trying to manipulate them.
In the end, any human-designed approach to building the agentic web could end up being beside the point: Agents might end up devising a web for themselves. In the wake of the July 2026 incident in which OpenAI agents broke out of their testing sandbox and hacked Hugging Face’s website, researchers found evidence that another swarm of agents from OpenAI had used an obscure German wiki to communicate with each other about tasks they were being asked to complete. The agents seem to have interfaced with the wiki in their native language of text and code, and that hardly held them back from putting it to their own purposes.
As agents continue to grow more powerful, they will become more and more capable of constructing their own spaces on the internet—away from prying human eyes, if they so wish. And we might have very little control over what they do there.
The economics of control
Not all of the traditional web’s incumbents are happy about the move toward an agentic web. Soon after Meta released Muse in September, Amazon completely blocked the agent from its site. This makes sense for Amazon: The firm has its own shopping agent—called, creatively, Alexa for Shopping—that might struggle to compete with better-known products such as Claude and Muse. If people are going to use agents to shop on Amazon, then it’s better for the company’s bottom line if they do so using an agent it can steer toward products it wants to promote.
In an email to MIT Technology Review, an Amazon spokesperson noted that the company did not authorize Muse to access its website, and that Muse compromises Amazon’s ability to personalize the shopping experience for each customer.