I have the privilege of being the executive sponsor of Fullstory.com. We’ve seen the volume of bot traffic to our website increase significantly in the past six months, which correlates directly with the rollout of tools like Claude Code and Cursor. These tools have led to a greater number of agents visiting, consuming, scraping, and interacting with our digital experiences.
We’ve historically just lumped all bot traffic in a category of bad or utilitarian, but that is changing now as helpful, non-malicious agents start visiting, interacting, and in some cases purchasing on behalf of customers and consumers.
We’ve all built processing, measurements, and guardrails around this traffic, but it’s also fundamentally changing the measures of site health that may go beyond a traditional cursory check of Lighthouse scores.
Your teams probably check load time and page speed regularly, validate and test mobile and responsive layouts, and maybe run an accessibility scan. You check to make sure the experience looks solid, navigation is intuitive, and the forms work.
The problem is that traditional tests and measures are about human user experience. Few people are considering an increasingly crucial question during website audits: Can an AI agent actually “see” this experience? Does it know what each element is, what each page means, and what action to take next?
That gap between what human visitors experience and what machines content actually parse is growing more consequential by the day.
Check your agent experience score →
Why AI agent experience is crucial now
AI agents aren't hypothetical anymore. They're navigating websites, filing support tickets, completing checkout flows, and interacting with customer-facing products on behalf of real users. LLM crawlers are indexing content at scale, building structured representations of the web that shape how models understand your brand, your products, and your value proposition they are informing and biasing critical LLM searches more so now than traditional SEO ever did. And behavioral analytics platforms are capturing interactions, triggering automations, and powering personalization based on what they can observe and label in real time.
All of these systems rely on the same underlying infrastructure. And for most websites, that infrastructure is surprisingly incomplete.
Most AI moves fast. But without the right structural signals to orient itself, it still gets things wrong—it misidentifies elements, misreads page intent, and misses the context that would let it act or interpret correctly or more deeply.
The problem isn't the AI. It's the site data.
The fundamentals of agent digital experience
Agent experience isn't about whether a bot can load your page. It's about whether the page communicates meaningfully once it does. There are five distinct signal types that determine this.
Element identity
Interactive elements—buttons, links, form fields—need stable, machine-readable identifiers to be actionable. Without them, an AI agent navigating your site is working without labels. It can see the button. It can't know what it does. aria-label attributes and custom data-* identifiers are the foundation here. They're also what behavioral analytics tools use to differentiate a "Get demo" click from a "Log in" click. No label means no signal—and no signal means no meaningful data.
Semantic structure
HTML gives you structural tools that most pages underuse: <main>, <nav>, <header>, <footer>, <article>. These landmarks tell AI where content starts and stops, what's navigation versus body content, and how the page is organized. A single, well-placed H1 gives AI an anchor for the page topic. A page without semantic structure is a page without road signs. Agents can traverse it; they just can't navigate it with intent.
Structured data
JSON-LD schema markup tells crawlers and AI models what your content is, not just what it says. An article without structured data is a wall of text. The same article with schema is a typed object: author, date, topic, and content type all attached before a model reads a single word. Open Graph tags play a parallel role, shaping how your content gets previewed and summarized across AI systems and social platforms.
Navigation legibility
AI agents navigate by intent. They follow links because labels tell them where those links lead. Generic anchor text—"click here," "learn more," "read more"—erases that signal entirely. Descriptive link text and properly labeled navigation regions let agents move through a site with purpose. Without them, they're guessing.
Page identity
Every page should announce what it is before a machine parses the body. A well-formed title tag, a substantive meta description, and a lang attribute on the root element are small signals with outsized impact. They're the briefing an AI reads before entering the room. Missing them doesn't break anything visibly. It just means every session starts without context.
The behavioral data connection
AI agent experience and behavioral data quality are inherently a connected problem space.
When Fullstory captures user behavior through Fullcapture, the richness of what it can surface depends directly on how well your site's elements are identified and structured. A button with no name is a data point with no meaning. A navigation region with no label is a segment that can't be isolated. A page with no schema is a session that starts as a blank slate.
The teams getting the most from their behavioral data are the same teams whose sites provide clear, stable structural signals. That's not a coincidence—it's infrastructure. Better decoration means cleaner segments, more precise automation triggers, and AI that can act on your site with confidence rather than approximation.
Most AI waits for problems to escalate before acting. Fullstory catches them in real time, but only when it can see behavior clearly enough to understand it.
And the beauty of today’s Claude/Cursor-enabled workflows is that improvements in this area do not have to be a massive, resource-intensive undertaking. Fullstory has the tools and guidance as part of our onboarding to ensure your site and products are ideally decorated to provide the depth you (and AI) want and need.
Where to start
If you're not sure where your site stands, we built a free tool to surface it: the Agent Experience Index. Submit your URL and get a scored breakdown across all five dimensions, with specific findings and prioritized recommendations.
→ Try it now: Check your agent experience score.
A few patterns tend to have the highest return regardless of where a site starts:
Add aria-label to interactive elements. Buttons, links, and navigation regions. This single change improves both AI legibility and accessibility coverage simultaneously.
Implement JSON-LD on your highest-traffic content types. Even basic Organization and WebPage schema moves the needle for how AI systems understand your content.
Replace generic anchor text. "Click here" and "learn more" cost nothing to fix and degrade every machine that tries to navigate by intent.
The sites that perform best in an AI-native world are the ones that communicate most clearly to machines while still delivering the experience humans expect.
Both are achievable. Most sites just aren't doing both yet.
