LLMs are quickly changing how content gets discovered. Publishers and website owners are responding in kind, seeking to control how their content is used. With llms.txt being introduced - a proposed machine-readable file designed to communicate usage preferences to AI crawlers - content control become more feasible. The llm file faciliates AI info, much like how the robots.txt file faciliates traditional web indexing.

Its all about signals​

The llms.txt file lets website owners signal how they want their content to be used when responding to LLM queries. For example, a publisher might specify that their content can be crawled, but note that it should not be used for long-term model training. Other publishers may allow only excerpts to be used in responses. Some publishers may even be more script.

If you’ve ever worked with developers to improve website behavior, like handling pop-ups, forms, or product filters, they were probably using React. It’s a popular tool for building modern websites (to say the least). But when too many pieces of a site need to work together, the process gets chaotic fast.

Developers help resolve this by turning to Redux - a Javascript tool that pulls scattered data into one place and makes it easier to coordinate. Its not an elegant process but it produces consistency and control, especially when in comes to interactive experiences. It's also why Michael Antzack believes the centralized state wins.

That same logic is now starting to show up in how brands think about visibility and coordination in the age of LLMs.

The Goal: Build a Stack That Performs:​

• LLM citation scans: to identify where your brand is being referenced in AI-generated answers across LLM tools, and how often it appears.
• Prompt recall tests: to evaluate how well your content shows up in response to common AI prompts, and whether that content is accurate.
• Linkless mention tracking: to spot brand mentions that appear in forums, summaries, and AI outputs even when there’s no backlink.
• Crawlability for AI bots: to check if your content is accessible to AI-oriented crawlers and isn’t blocked by rendering issues or robots.txt settings.
• Pull in: search-generated citations and prompt-level results using browser automations and n8n scripts.

The Recipe​

🧪 1. Prompt Recall Tests​

Test whether your content appears in response to relevant prompts.

Manual Testing:

• ChatGPT Plus ($20/mo) – GPT-4o for manual recall tests

Automation (optional):

• Playwright or Puppeteer – Browser automation for simulating prompt entry across tools
• n8n – For scheduling and orchestrating prompt runs
• Claude API or OpenAI API – To score results for accuracy and brand inclusion

The era of static rankings is coming to an end. If your SEO strategy is still focused on capturing the number one position for a specific keyword, you’re preparing for a bygone era. AI driven search using LLMs is reshaping the landscape.

Now, brand visibility in LLMs isn’t a straightforward outcome; it’s a probabilistic one.

When someone requests a product recommendation from an LLM, the response hinges on much more than just the text of the query.

User intent, context, and even minor phrasing differences can drastically influence which brands get recommended. This is because there’s no one size fits all answer for something like “What’s the best mattress?” or “What’s the top marketing tool?” Hundreds of different recommendations could come forth based on who is doing the asking, as well as how and when they ask.

Welcome to what Garrett Sussman calls Probabilitic Visibility

The Generative Search Ratio (GSR) is a new metric that developer Todd Gray has proposed to assess how discoverable a brand is within environments driven by large language models (LLMs).

As businesses contend with the shift from traditional search methods to those powered by generative AI, they must now ensure visibility not just in Google rankings but also in the synthesized responses provided by LLM tools like ChatGPT and others.

What is GSR?​

The GSR serves as a way to quantify this new kind of digital presence, helping brands understand their positioning in this emerging search landscape. It basically assesses the relationship between your visibility in large language model (LLM) responses and your performance in traditional SEO.

The basic formula is: GSR = (GEO Score × Visibility Weight) / SEO Score

When someone asks ChatGPT, Perplexity, or Claude a question, where does the answer come from and how often does it come from you?

As LLMs replace search engines for top-of-funnel research and product discovery, a new visibility layer is emerging: citations. AI-generated answers increasingly include footnotes, source links, or inline references to websites, articles, and documentation. These citations form a kind of modern backlink but with different mechanics and consequences.

And that brings us to a new idea: Citation Score.

What Is Citation Score?​

Citation Score is a way to measure how frequently and how prominently your brand, product, or content is cited by LLMs across a set of relevant queries. Think of it like domain authority, but instead of measuring how many other sites link to you, it measures how often LLMs mention or reference your content as part of their synthesized answers.

A basic version might include:

• Citation Frequency: How many times your content appears across 100 high-intent questions?

• Citation Position: Are you the first link? Buried in footnotes? Cited inline?

• Citation Context: Are you cited for facts, how-to instructions, product comparisons, or definitions?

Over time, these could be modeled into a visibility index that SEO teams and brand strategists can track.

As AI tools become more acccessible, app development has become easier. SEO professionals are starting to apply their expertise to build practical applications. One such professional is Deyan Georgiev from Toro Rank. I recently asked him to discuss an innovative app he built.

What does your tool do, and why should we care? (spoiler: we should)​

The tool I built addresses two problems I see often while working with clients. Businesses are missing content opportunities and accidentally hurting their SEO with off-topic content just to get more traffic, or their SEO guy/agency can validate their invoice. Interviewer's note: Use Serper API with app.

What Is an LLM Visibility Specialist?​

An LLM Visibility Specialist is someone who helps content get recognized by large language models (LLMs), such as ChatGPT, Claude, and Google AI Overviews. They combine writing, strategy, and lightweight technical tools to improve how frequently a brand is mentioned in AI-generated answers.

This new role is gradually emerging as search behavior shifts toward LLM platforms. It builds on traditional content writing and SEO but goes a step further by focusing on how to structure content so that AI tools select it as a reliable source.

Why It Matters for Content Writers​

For content writers, this shift means your job doesn’t end at publishing what’s useful. The real opportunity lies in learning how LLMs interpret your content. From there, you’ll have to change how you write, structure, and track performance to fit that behavior. If someone asks ChatGPT about a problem your content solves, your goal is to make sure it’s your content that gets cited.

Top-of-funnel and middle-of-funnel content is the primary focus here, but bottom-of-funnel content may not be far behind. This blog post is the first one I’ve written with this focus in mind. And it probably won’t be the last.

So my Clearscope-style tool is workable. I almost had a meltdown from coding frustration but pulled myself together and got it done. Still, its time to compare my original goals with how well it performs now. So I compared my main.py code page with goals and asked ChatGPT for an evaluation.

Turn your SEO strategy into a growth engine​

You want to be strategic when it comes to planning content. If you're serious about promoting growth, here's a smart framework to use:

Begin with BOFU​

Do not divert your attention from bottom of funnel pages until they rank and convert. They are the ones that directly drive sales.

WIth BOFU content, make sure you:

• Target the most high intent keywords
• Check that your site has fast load times
• Your site is fully functional on all devices
• Optimize your headers and meta descriptions
• Present compelling calls to action