There is a new kind of visitor on your website, and it does not have eyes. AI browsers, ChatGPT Atlas, Perplexity Comet, Gemini in Chrome, Copilot Mode in Edge, increasingly arrive on a page not to read it the way a person does but to extract facts, compare options and, in agent mode, click through a task on the user's behalf. Cloudflare and others have clocked roughly a 6,900% jump in requests from AI agents and agentic browsers since July 2025. That is not a rounding error in your analytics, that is a new audience.
The awkward part is that most websites were built for one reader: a human with a cursor, scanning a layout. An agent does not care about your hero animation. It cares whether it can find the price, trust the answer and complete the action without getting stuck. A site that delights people can still be effectively invisible, or unusable, to the software now browsing on their behalf.
The good news: getting agent-ready is mostly hygiene, not a rebuild. Here is what actually moves the needle.
What an AI browser sees that a person does not
A human lands on your page and forgives a lot. They infer that the bold number is the price, that the button in the corner is checkout, that the testimonial is marketing. An agent infers none of that for free. It works from the structure underneath the design: your HTML semantics, your headings, and above all your structured data.
That is why the single highest-leverage move is strong, accurate schema markup. Organization, Article, Breadcrumb, Product, FAQPage, whichever fit your pages. Schema is the difference between an agent guessing what your page means and being told. If your prices, availability and key facts live only in styled text, an agent has to reverse-engineer them and will sometimes get it wrong. If they live in structured data too, there is nothing to misread.
The first 150 words do a lot of work
Agents and AI search engines weight the top of a page heavily. Front-load the direct answer to what the page is about in the first paragraph, then expand. Burying the conclusion under three scrolls of preamble is now a ranking and comprehension problem, not just a UX one.
The agent-ready checklist
You do not need all of this on day one, but each item makes your site easier for software to read and act on:
Structured data on every important page. Validate it. Wrong schema is worse than none because it actively misleads.
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Clean semantic HTML. Real `
/hierarchy, realand` elements, descriptive link text. Agents lean on the same semantics that screen readers do, so accessibility work pays off twice. Front-loaded answers. State the key fact, price or conclusion early on each page.
An
llms.txtfile. A simple, machine-readable map of your most important content. We covered the why and how in our guide to llms.txt.Fast, server-rendered content. If the fact an agent needs only appears after heavy client-side JavaScript, many crawlers will miss it. Render it on the server.
Sensible crawler rules. Decide deliberately in
robots.txtwhich AI crawlers you welcome. Blocking all of them can quietly erase you from AI answers.
This overlaps heavily with classic technical SEO and with generative engine optimization, which is the point. Work done for agents is rarely wasted on humans or search engines.
WebMCP: the next step past "readable"
Reading your page is one thing. Acting on it reliably is harder, and it is where a real standard is now forming. WebMCP, going through the W3C and shipping in Chrome 146, lets a website publish a set of structured tools that an agent can call directly, "search products", "add to cart", "book a slot", instead of trying to drive your UI by clicking around and hoping the DOM does not shift under it.
Think of it as an official back door for trusted agents. Instead of an agent screen-scraping your booking form and fumbling a date picker, it calls a checkAvailability tool you defined and gets a clean answer. For anyone running a booking flow, a storefront or a configurator, this is the difference between agents completing tasks on your site and abandoning them. It is early, but it is the direction of travel, and it builds naturally on the same Model Context Protocol foundations we have written about before.
If you sell online, this is already commercial
For e-commerce the stakes are concrete and near-term. Shopping agents do not browse your beautifully art-directed category pages. They evaluate product feeds and execute against checkout APIs. The fields that decide whether your product is even considered are unglamorous: name, brand, price, real-time availability, GTIN or MPN, return policy, shipping details, reviews. If those are incomplete or stale, an agent quietly skips you in favour of a competitor whose data is clean.
Standards like the emerging agentic-commerce protocols are racing to define how agents query catalogs and complete purchases. You do not have to bet on a winner today, but you do have to keep your product data complete and your checkout reachable by an API, not just by a human clicking buttons. We go deeper on this in agentic commerce and what it means for online stores.
How to start without boiling the ocean
Run one test before you plan anything. Open ChatGPT or an AI browser and ask it to find a business like yours, summarise what you offer, or complete a simple task on your site. Watch where it stumbles. That five-minute exercise will tell you more about your gaps than any audit, because you see your site through the new visitor's eyes.
From there it is a short, ordered list: fix the structured data on your top pages, front-load your answers, publish an llms.txt, make sure the important facts render server-side. None of that requires a redesign, and all of it helps your human visitors and your search ranking too.
If you would rather have someone audit your site for agent-readiness and hand you a prioritized fix list, that is exactly the kind of work we do. The sites that get this right early will be the ones agents quietly recommend while everyone else wonders where their traffic went.
