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Most marketing teams still picture search as someone typing a few words into a prompt or search box and getting a response, whether a paragraph with citations, as an LLM does, or a traditional ten-blue-links result. This search paradigm will become obsolete faster than anyone expects. The AI personal assistant, Instinct, is growing at 10% per day without any marketing spend, and I am certain more products will enter this space soon.

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I have been using the Instinct in my messages and WhatsApp, and its responses are nothing like what Gemini or ChatGPT would ever output. I am also using GrokBot on my desktop, and I am hooked.

Behind the scenes, an agent runs a dozen queries you will never see, reads the pages it likes, ignores the rest, and hands back a short answer with ideas and recommendations attached. I never see a results page, and the sites it scrapes have no idea they benefited me. Even if I converted on any of the recommendations, the product or service provider would never know where the journey started.

SEO is more important than ever

Yet agent searches still rely on websites, and getting websites into those agent responses depends on SEO more than ever. For marketers, this creates a huge challenge: how do you do SEO for agents when you don’t know whether your efforts are working?

This changes what you optimize for in ways that make most SEO playbooks completely obsolete. The fundamentals and best practices survive, but the tactics need to change. The entire toolset will also struggle to meet the new requirements. Knowing the keywords people might use in a traditional search engine, and the monthly search volume for those queries, won't be very helpful in an agent-dominated world where requests might not even use words.

Don’t start with keywords

So the first thing to drop is the keyword list as the foundation of the strategy. I have written this recommendation many times over the last few years, but it’s even more relevant now. The only starting point is the job the customer is trying to get done, described in their terms and not yours. If you sell products on an e-commerce website, the job isn't “the product name,” and never was, because the job is to fulfill that product's functions. When I consulted with WordPress, much of their SEO effort focused on the biggest keywords in their website-building category. When we pivoted to the user's needs- a website for a realtor, a restaurant web presence- we saw an immediate uplift in traffic because that was the “job.” An assistant working on that job will look for anything that credibly solves it, and it will not care whether your page is titled with the right phrase or how many times you used a keyword.

These AI systems are built very differently from how a ranking algorithm scored pages for the last two decades. An assistant reads to extract an answer, so a page that spends 1,800 words rambling without saying what the product is will get ignored.

Local services as an example

Consider a local search for a plumber to install a new sink.

The user opens their AI personal assistant, uploads a picture of the new sink, and says, "Find me someone who can install this within the next week." The AI agent knows the user's location and can determine the skills needed for the job.

Now let’s compare the vendors that the agent will recommend:

• Vendor #1 has named their business “Best Plumber Near Me”, has a website built by the best keyword-stuffing SEO agency in the area with detailed diagnostics on sinks, has hired an agency to build reviews, and has just recently onboarded an agency to astroturf citations.

• Vendor #2 has a one-page site about the service provider, and has hours, prices, and services. In a traditional SEO world, this web presence would be a total failure, but in an agent-centric world, this vendor would have everything the agent needs to recommend them.

• 

Now put yourself in the agent’s seat. It has a photo of a sink, a zip code, and an immediate request. It doesn't care that Vendor #1 has four hundred blog posts about faucets and a page for every sink manufacturer. In traditional SEO, those niche posts might have generated a click, but now they are all aggregated as sink content, none of which helps the user in the moment.

Vendor #2 wins this visibility in the agent response. The page says what they install, what it costs, which neighborhoods they cover, and when they pick up the phone. An agent can lift every one of those facts in a second without guessing. Vendor #1 forces the agent to dig through a thousand words of how-to content to figure out what is that the vendor does.

Content is only half the test, though, because the agent also has to act. Someone who wants a sink installed needs availability, a way to book or a number to call, and prices the agent can verify. If your page makes the agent guess at any of those, it will pick the vendor that offers everything it needs.

What Vendor #2 lacks is proof from someone other than their own website that they can do that service. A page can claim reliability all day long, but every business can. To confirm the recommendation, an LLM, and in this case an agent running multiple queries, looks for corroboration of its conclusions.

In this case, it’s not just citations that vendor #1 astroturfed on Reddit; rather, the agent is looking for a listing with the local trade association, a neighborhood forum like a Nextdoor thread where a homeowner thanked the plumber by name, a mention in a small-town newspaper, or Yelp/Google reviews that sound like people who actually got a sink installed.

As you can imagine, one real mention on a site the agent already trusts beats fifty manufactured ones. Don’t forget how easy it is for AI to detect AI. An LLM can tell when all reviews share the same sentence skeleton, the same adjectives, and a suspiciously cheerful tone.

Citation building for AI agents

Now that you can't count visible citations in an LLM response and call it a win, the citations that matter in this new world are the ones that actually drive the assistant's decision-making. That’s marketing, not easy SEO manipulation. Link building was about passing authority from one site to another, and the goal was to increase the number of backlinks. The industry extended that to AEO with similar metrics, but with personal agents, it’ll be much harder to count vanity activity.

Measurement

Measuring SEO impact has always been tough. As AI has become more prevalent, attribution has gotten even harder, and with AI personal assistants, it will become almost impossible. But that’s OK. Brand marketing has never had a clean way to measure impact either, yet major brands still spend billions on the channel. Measuring the impact of SEO efforts that underpin agent responses will now require logical explanation and trust on faith rather than hard data. Storytelling will matter more in this new future than running complex data studies on data that might not exist.

As an industry, it is time to stop demanding last-click attribution from a channel that no longer has a click. I shared a few weeks ago how to measure this channel, and it still holds true for agents. I won’t rewrite that whole post here, so check it for yourself.

With personal agents, AI will move from a novelty and an efficiency boost to real disruption. If you aren't using a personal assistant yet, check it out, and you will see how quickly it becomes addictive, which is how users will experience it, too.

SEO is more necessary than ever, so now is the time to invest in the right efforts before you are completely disrupted. Continue following best practices, understand the Job-to-be-Done, and most importantly, build your website and content with the user at the center.

How to execute this playbook will be completely custom for every company and product because the strategy is built around each customer's nuances. (Reach out if I can help.)

Companies and marketers that build for this new use of AI in a truly user-centric way will stay well ahead of competitors still trying to adapt traditional SEO into AEO with the same tactics, just under a new name.

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Ranking on Google doesn’t guarantee a mention in AI answers.

Bitly already had the brand recognition and SERP footprint. We helped them earn citations through the other channels LLMs trust.

Over twelve months later, Bitly now holds 11.7% of AI citations for link shorteners — close to double the next competitor.

Through a Reddit-first GEO program powered by data from hundreds of buyer prompts, our AI visibility experts helped them:

• Turn a dormant branded subreddit with 38 members into a content library Bitly owns outright.

• Create 130+ live Reddit URLs that work as evergreen assets for search and AI answers

• Earn AI Overview citations for 8 Reddit threads (4 of them in a top spot).

• Grow Reddit referral sessions to bitly.com from 178 to 930 in 12 months

Want to know WHY your brand is missing from AI answers?

Foundation Marketing uses buyer prompts and data from AirOps, Ahrefs, Semrush, and other AI visibility tools to find the gaps that you can close on Reddit, YouTube, Review sites & more.

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• Think beyond just the top Subreddits. All subscribers can download a list of the top 100 Subreddits; paid subscribers can download the top 10,000.

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Here’s a list of the top 100 Subreddits. Paid subscribers can access the top 10,000 subreddits that are behind the paywall.

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Before you start

You’ll need a Google account with access to the Search Console property you want to track, and Editor access to Google Drive to upload a file. Nothing here requires a paid Google Workspace plan. The whole thing runs on a free Google account.

Step 1: Convert the file to Google Sheets

Upload the Brand_Search_Trends_Tracker.xlsx (linked below) to Google Drive. Double-click it, then in the preview screen, choose Open with > Google Sheets. This creates an editable Sheets copy. Apps Script, which powers the automated Search Console pull, only runs inside native Google Sheets, not inside an Excel file sitting in Drive unconverted.

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This week’s newsletter is sponsored by Foundation Marketing and Ahrefs.

• Paid subscribers can download this Python crawler, which calculates the click depth of your pages, and check out this post for my roadmap template.

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Much of SEO has changed with the introduction of AI, and link building has not survived the transition unscathed either. I believe most of what passed for link building over the last decade was already obsolete before AI-assisted search showed up. A lot of link building was built around manufacturing signals rather than earning them, and over the last decade, Google has significantly improved its ability to detect and ignore these sorts of links.

[Sponsored by Ahrefs]

Another great new feature launch from Ahrefs.

"Ask Ahrefs" is now live and can be accessed on any Ahrefs page.

It reads the page you're on and your whole workspace. So you can ask it to: → summarize what's on screen → compare your site to a competitor → explain why your mentions spiked last week.

It's an agent, not a chatbot. It runs its own API queries, navigates the tools, and applies filters to get the data instead of asking you to.

Free for Ahrefs users while in beta.

Regardless, the discipline of link building done properly is still very much alive, and I will write a future post on what that actually looks like today, but that is a different argument for a different week. What I want to go deep on right now is the category of links that are the easiest to acquire and carry an outsized impact on everything else you are trying to do in SEO: internal linking.

What are internal links?

Internal links are internal references to pages within your site. Writers insert them to get people to read more content, but search engines understand them with the same algorithms they use to understand external links to your site. Instead of building authority from other sites, they build topical authority within a site. They are significantly easier to manipulate and obtain than external links.

Nobody has to negotiate a rate with an outreach agency working off a spreadsheet of domains and hope the receiver on the other end actually responds. You already own every one of these links, and most companies are sitting on far more unused authority than they realize.

Technical SEO has diminishing value in improving a site’s traffic because even a site with terrible structure can do well as the underlying AI in the algorithms will unwind bad best practices. Internal linking is the exception. I have never worked with a large website that couldn’t benefit from better internal linking.

Two reasons internal linking matters

1. The PageRank logic: every page is weighted by every page linking into it, and those votes are then logarithmically counted to pass authority to a new page. Therefore, a link from your homepage carries more weight than a link buried eight pages deep.

2. Internal links are how content gets discovered in the first place, by crawlers and now by AI systems trying to understand what your site knows. A page with zero internal links pointing to it is an orphan, and orphaned pages are functionally dead even when they're indexed, because nothing on your own site vouches for them. If nothing on your own site vouches for a page, don't expect an AI answer engine to go find it and vouch for it either. A page can be indexed and functionally invisible at the same time.
   
   Click depth is critical because a page that takes five clicks from the homepage to will be crawled far less frequently than one that is closer to the homepage. My opinion is that any important pages should live three clicks or fewer from the homepage.

How to fix internal linking

Generally, new content constantly links back to old content because you reference the foundational piece, you cite the earlier post, you build on what already exists. The reverse almost never happens. Old content doesn’t get updated to link forward into new content, because that requires someone to remember the old page exists and go do the work. Therefore, authority flows backward in time, while everything published this year sits there starving for the links that would actually help it rank or get cited.

Treat every page as a candidate for cross-linking. This must be built into the publishing workflow to update old pages, or ideally build dynamic logic that automatically inserts links into older pages on a schedule so there’s less manual work to do.

Context doesn’t matter as much as you think

Too many teams aim for context in internal links, which isn’t necessarily bad, but it misses the whole magical point of these links: driving more discovery. Focusing only on contextual relevance creates a biased feedback loop because your most popular topic already has the most content.

Popular links to popular. Niche stays niche forever, because the internal linking logic never gives it a shot.

To fix it, break it on purpose by ignoring context. Inject randomness into the linking logic, and I mean structurally engineered randomness. You can have dynamic logic on a page that inserts new content in a link box, but your logic must link to random pages.

This is obviously not the best editorial link strategy when a page about pricing suddenly links to a product launch blog post from eighteen months ago, but it will work. This needs to be truly random, so every page has a chance to be exposed to internal links.

A massive (millions of pages) site I worked on that did this saw crawl, indexation, and most importantly, traffic improve dramatically within weeks. Pages that had sat flat for over a year with zero internal links pointing to them got crawled again within days of turning on random link injection, and a meaningful chunk of them doubled organic traffic shortly after, without a single word of the content changing.

Server-side only

Ideally, any logic you use to build these links happens on the server because otherwise your links could be invisible to search engines. If your site runs on any JavaScript framework that renders links client-side after the page loads, it’s highly possible that these links will be invisible to crawlers and AI systems. Minimize this risk by making the links render server-side.

How you know it’s working

Once your new link algorithms are in place, pull crawl stats from any log analysis tool and run a crawl to compare your orphan page count before and after. If traffic to old pages starts moving without anyone touching the content itself, you can chalk this up to your linking efforts. Internal linking is the one thing in SEO that you can never invest too much in, so if you are looking for some low-hanging fruit, go pick this one.

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94% of B2B buyers now use AI when researching software. So who’s AI citing when they look for tools like yours?


Well, it’s usually not you. We analyzed 57 million citations across 50 brands: only 2.2% of citations on early-stage buyer queries pointed to brand-owned domains.

Your SEO, PR, and social don’t fix this on their own. And we’ve learnt over the last 12 months that getting cited by AI is its own discipline. The Hidden Selection Phase report shows where AI pulls its answers from, and what separates the brands it cites from the ones it skips.

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Getting itchy and instead want to see where your brand stands? Book a call for a free content audit with the leading AI visibility agency for B2B.

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Email me with questions or problems accessing the script.

Getting this running takes about five minutes on any machine with Python installed, and there’s no real “deployment” required since it’s a script you run once and let finish, not a service that sits on a server.

First, confirm Python 3 is installed by running python3 --version in a terminal. Anything 3.7 or newer works fine.

Next, install the two libraries the script depends on:

pip install requests beautifulsoup4

If that fails with a permissions error, add --user to the end of the command, or set up a virtual environment first with python3 -m venv venv followed by source venv/bin/activate on Mac or Linux, or venv\Scripts\activate on Windows, then run the pip install again inside that environment.

Save the script file somewhere accessible, then run it against the site in question:

python3 click_depth_crawler.py https://yoursite.com

That’s the whole deployment. It runs locally on whatever machine you launch it from, whether that’s a laptop or a server you SSH into, and it reaches out to the target site over normal HTTP requests the same way a browser would, so there’s nothing to install on the site’s side and no code to add to the site itself.

A few flags matter depending on the size of the site. For anything with more than a couple thousand pages, raise the ceiling before running: python3 click_depth_crawler.py https://yoursite.com --max-pages 10000. If the crawl feels too slow, the delay between requests can be lowered with --delay 0.1, though pushing it too aggressively risks tripping rate limiting or bot protection on the target site, so raise it in small increments rather than dropping straight to zero. Output lands in a file called click_depth.csv in whatever folder the script was run from, unless a different name is specified with --output filename.csv.

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This week’s newsletter is sponsored by North Star Inbound and Semrush

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