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For years, gray-hat SEO had little chance of affecting a company beyond its Google visibility. Overstep the limits of spam? Google levied a penalty, but it only affected visibility on Google, not any other channel. Get a backlink on an adult site? No one would ever see that unless they looked at a backlink tool, and no one outside of SEO does that.

AI changes everything

When marketers, agencies, and AEO tools put a marketing claim on any website today, those don’t just have the ability to influence an invisible algorithm; they are also fodder to be restated in an LLM output. The training pipeline doesn’t distinguish between The Wall Street Journal and a series of random blog posts that seem to support a consensus opinion, because it has no concept of domain authority. I have seen citations from sites that would never have mattered as a link in traditional SEO. Everything it finds goes into the model and can be pulled back out as citations when someone asks a related question.

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This whole input-output effect sounds abstract until you understand what it actually means for brands: those citations, wherever they came from, can come back out of the system as fact when someone asks about a company. Those searchers could just be users forming an opinion, but it could also be an analyst, journalist, investor, or the CEO of a potential acquirer. The LLM response presents these marketing claims with the weight of sources (the SEO planted citations), and it feels like the truth to the searcher.

The difference between aggressive marketing copy on a website in a pre-AI world and that same claim making it into an LLM is distribution. The website was only seen by those who visited the page, while the LLM reaches the whole world and presents it as sourced fact.

(statements like the one below sourced to Reddit could cause issues when these companies are public)

SEO slop has now entered the PR conversation

At most companies, PR and SEO never get in the same room to discuss strategy. I say most, even though in my experience it’s all, because I hope there are exceptions. PR and SEO have different budgets, mandates, and strategies. Usually they’re in different departments reporting to different mid-level executives, even if they are both in the marketing department. PR reports to comms. SEO reports to a director of marketing or growth. The incentive structure makes them competitors for budget and attention, not collaborators. PR cares about controlling the narrative while SEO cares about visibility.

Parallel goals don’t work anymore.

In today’s AI-first world, the content the SEO team creates may make claims that would give a PR team a heart attack. These claims might compare a company favorably to a competitor in a way that’s technically true but aggressive. “Best” is a fantastic keyword, but PR teams don’t like to use absolute terms like that without a qualifier. Other claims might describe a market position in defensible terms, but not how they’d be described to investors. “ Used by 99% of the Fortune 500" is great in social copy, but in an investor presentation you would qualify it by how many of those users are currently active or have ever paid for an account. Generally, SEO makes claims about technology or traction optimized for search intent or sales, not for a media deck.

From an SEO standpoint, none of this is intentional deception because SEO results have always rewarded claims that match what people are searching for, not claims that match a company narrative. In fact, if an SEO team had to take marching orders on SEO from PR, they would have limited SEO success. I once had a consulting client who couldn’t use their primary keyword in their homepage title tag because the PR team had invented a new word they insisted be used. Only that team ever used that word.

With only an SEO north star, the team might create content about why a product is the best because it matches a supposed high-volume search query, while a PR team would phrase it differently so it’s not perceived as fact. PR teams hedge and don’t speak in terms of absolutes. SEO teams never cared for that nuance.

AI merges PR and SEO

With the work SEO teams do to drive LLM visibility, a company now has citations in multiple places saying something mostly true, but not entirely. When the LLM cites these claims, industry bloggers can pick them up. A small inaccuracy spreads far and wide because an LLM trained on all of this learns the claim is real because it’s everywhere.

It doesn’t stop with just bloggers. When a market analyst searches for information about a company before an earnings call, the AI response surfaces this SEO-planted framing and could ask a related question during the call. Imagine that CEO being forced to answer a ridiculous question coming out of nowhere. The CEO will fire off an angry text to the CMO, who will point to the PR team, who will then blame the SEO team. Where SEO used to be an afterthought ignored by the executives, now it will be the center of attention, but not in a good way.

This isn't hypothetical; I have already seen and heard it happen. Companies are starting to realize that SEO teams (and likely their external agencies and teams) have been building citations for LLMs around claims that should never have survived a PR review.

Now the real nightmare begins because it can’t be undone.

You can remove some citations, but you can’t get them all. The ones under the SEO team's control might be deletable, but the ones that aren't are out in the wild. Even after you’ve deleted everything you can find, LLMs trained on historical data already learned the pattern. The next generation of models will have seen the claim repeated across so many sources that it becomes more credible, not less. Retraining an LLM is AEO in reverse, and as anyone who has tried their hand at AEO knows, there are no guarantees. As of yet, no playbook exists for AEO reputation management for big brands.

This will be especially problematic for public companies because they need to control their messaging or run afoul of regulators. Public companies have built an entire infrastructure to control their narrative, and aggressive SEO tactics will now undo it. Reddit spam can actually impact a company’s share price.

Companies already experiencing this need to start undoing it right away; it will not be fun work, but for others who haven't made this mistake yet, there is time to alter course.

The fix

Companies that keep running AEO as a standalone SEO motion will create problems. The SEO team will get AEO results, but they won't translate into business results. When everything hits the fan, the SEO team will take the fall. Companies will start pulling budgets from agencies and teams that create reputational risk, and they’ll start hiring teams that understand the cross-functional problem.

This isn't a 2028 problem. If the SEO team is building AEO strategies right now without PR input, those citations and future problems are already in training datasets even if you don’t see it yet. SEO and PR need to collaborate, not the old way where they just approve blog posts. PR needs to understand what the SEO team is doing, and the SEO team needs to understand the PR message. AEO has to be built around the company narratives, not the other way around.

AEO is a brand challenge as much as, if not more than, it is a search challenge. It might take a disaster for companies to finally realize it. The messages LLMs put out matter more than clicks and conversions; they shape how customers, partners, and investors view a brand.

This is the moment when SEO teams and PR teams either start working together or start working against each other. Companies that figure out how to bridge that gap first will have a massive competitive advantage as AI continues to grow. Those that don't will spend valuable time untangling an AEO mess while competitors do actual business.

Be the former.

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I see a lot of SEO proposals and reports; most SEO firms are not being truthful to their clients. It’s 2026, and an agency is definitely not needed for the same reason it was in 2022 before ChatGPT popped onto the scene.

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The pre-AI-era agency was driven by a content model that drove the entire agency industry: a team of freelance or full-time employed writers churning out 500-word posts targeting long-tail keywords. The bulk of the agency margin was driven by this model because the agency could tack on 50%-100% on what the actual content cost them to produce. To adapt to AI, many of these same agencies have done nothing more than rename their content teams “AEO specialists.” These new experts do the same work as before, but they just swapped the word “keyword” for “prompt” because the client is not sophisticated enough to notice.

The truth is, if an LLM can write that article faster and cheaper than the agency writer, why do SEO agencies still exist? The answer is that it shouldn’t if this is all the agency does. This isn’t a new reality; rather, AI just made it impossible to hide.

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Content alone is not SEO

When it came to SEO, content was never the value an agency provided. In-house teams could also hire freelance writers and manage them. What the client really wanted to pay for was growth. The agency sold the monthly packaging, claiming that their agency process led to growth. Agencies delivered content because it was easy to scope and easy to hand over as a deliverable. Twenty articles a month, briefed, written, and delivered, is a lot easier to scope than the ambiguous “growth.” Some agencies sold guest posts for links, which is also just content, but on someone else’s site. This was just as easy to scope and deliver.

(I have already discussed technical SEO as an AEO deliverable in this post.)

For the growth KPI, they created and pointed to rankings dashboards. This appeared to be progress because it was measurable, and agencies kept their jobs when the dashboard was green. When the dashboard turned red, the agency was replaced with another that could deliver green dashboards. In reality, strategy was supposed to be the real value beneath it all, but agencies never had to prove that because the content itself was the deliverable everyone could see and count.

With the introduction of AI, the primary deliverable of content is worthless. Anyone with Claude access can produce better, meatier mediocre articles nearly autonomously than a typical agency team can ship in a quarter. This is why there are so many social media posts about firing agencies and replacing them with Claude. The core agency deliverable of dashboards and content can truly be replicated by a $20 Claude subscription.

To combat this client churn, now is the moment for agencies to pivot their offering and for clients to demand something new. For the agency model to survive, agencies should stop selling content immediately. A business paying an agency in 2026 purely to churn out blog posts is paying for something with less differentiated value than an LLM subscription. There is plenty of real work left that AI can’t touch, and given how many companies are distracted by AI FOMO, the right work is more valuable now than it’s ever been.

Strategy as THE deliverable

Strategy is the primary asset agencies should be selling. Real strategy means understanding why a business, with its ICP, should own visibility in problems its competitors haven’t yet figured out. This requires a deep understanding of the customer, the product, and the jobs-to-be-done. Doing this is hard work the internal team might not be able to execute on its own, which is why an agency should be brought in to do that heavy lifting.

An organization’s internal team might have customer support data, product feedback, and brand research, but they don’t know how to turn it into a compelling strategy they can execute to drive growth. The lazy way out of just using a keyword tool is the wrong approach. The same internal team can also purchase a keyword tool and make color-coded keyword plans.

They need an agency to do what they can’t do on their own and, most importantly, to turn it into meaningful growth. Companies can certainly bring these tasks and skills in-house, but there are many inherent benefits to using an agency, including instant access to talent (assuming the agency has it), flexibility, and scalability. Additionally, agencies working across multiple accounts will have insights that no single team or employee could access if they focus on only one company. Ultimately, the best option for many organizations might be to in-house these functions, but that is not an option for many.

PR as an agency effort

PR is the second focus area where agencies can help, and most SEO agencies have never done this. They bought links and guest posts, but didn’t deliver meaningful PR work, because that is hard. More than ever, PR is important because it will shape the brand perception reflected in LLMs as citations. An answer engine builds its response from sources with a track record of being cited elsewhere, so the same signal that earns a journalist's trust ultimately feeds an LLM

Getting mentioned in the answer an LLM gives someone requires the same thing as getting mentioned in the New York Times: a third party with credibility decided your brand was worth citing. You can’t fake your way into that with better technical SEO or an audit.

This is earned by being the source a journalist trusts, the founder who says something worth quoting, or the company whose data a researcher cites because it’s actually useful. SEO agencies spent years producing fake outcomes. I have seen past clients pay their way into the NY Times, but it was in places that never mattered for SEO and certainly not for AEO. Fake efforts no longer work when the goal is revenue. A guest post on a page no one, not a crawler or human, will ever see does not move any needles.

The agency of the future

To construct this sort of agency, it will look completely different. There are no writers on staff, or if there are, they’re doing original reporting and customer research, not grinding out keyword-stuffed posts that no one will ever read. This agency's output is not measured by articles written or links acquired; the actual deliverables are strategies, execution plans, and performance feedback. This agency conducts research and provides answers on how to win in ways the client could not achieve on their own.

The value of this agency is measured by its relationships with journalists and analysts, the way a PR firm would, except now that relationship directly determines whether an AI model treats the brand as a trustworthy source on a given topic. The agency coaches the client’s actual subject matter experts on what to say publicly, because those experts talking in their own voice on a podcast is worth more to visibility now than a hundred blog posts ever were.

The agency of the future is much smaller than the one it replaced, and it bills more like a strategic consultancy than one measured by words written or minutes in a meeting. Most agencies will run from this model because it's harder to scale and doesn't fit the model of driving margin with cheap labor.

These agencies will have to be truly creative and more agile than their clients to justify not being fired when clients in-source their basic deliverables or simply use a Claude subscription. The agencies that remain profitable in two years will be the ones that have figured out how to layer PR outcomes onto SEO logic and provide strategies that work in real life, not just in a slide deck.

Yes, agencies should exist, but the best ones will look nothing like today’s agencies. As always, reach out if you want recommendations.

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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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• 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.

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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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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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Over the course of my career, both in-house and as a consultant, I have worked with some genuinely exceptional SEO managers and in-house teams, people who understood the craft deeply, who built programs that compounded over the years with tangible business outcomes. All of those people share something that does not show up in most job descriptions, and the gap between what they do and what most companies hire for has only widened as the job has become more complex.

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SEO is not a checkbox

The version of the role that most organizations seek and what many of their SEO employees fill is a ticket-creating function. This SEO manager sits between the many different teams and functions as an SEO toll booth, blocking other teams' progress to lift product launches into Google’s stated best practices.

If a feature request horrifyingly violates one of these guidelines, the SEO team will prevent a launch for the sake of SEO hygiene. One of my favorite types of calls I do on Intro is when I get to be the one to give the green light to “just do it,” because every SEO “expert” a company has hired has blocked true business progress. The toll booth does not build anything.

The SEO toll booth has the glorious job of translating requests into Jira issues and then waiting to see what ships. They don’t initiate strategy beyond checking SEO boxes, and their reporting consists of sharing rankings and now prompting visibility as though summarizing data were the same as driving results. When asked to tie those dashboards back to business metrics, they just can’t. The job has drifted so far from what actually drives business performance; it’s no surprise to me that companies are shedding SEO teams as they shift to AI-first thinking.

The org holds it back

This is not a personal failing of the people in those roles, and I have met many who would like to shift their responsibilities, but they can’t. The structure itself is broken. SEO got attached to marketing org charts as a channel rather than a capability, so the best they could do in this role is “conduct” the work of other teams. Engineering owns the infrastructure, while product builds the roadmap. SEO is left with just telling those other teams what to do. This is just an SEO suggestion box with a title.

Some in the marketing world are trying to address this problem by applying different titles to the same role. Calling an SEO manager an engineer without changing any expectations or reporting infrastructure doesn’t change the outcomes. Likewise, giving SEO teams new external tools doesn’t change much if they still lack control over the internal levers that drive progress. A new title attached to the same broken structure produces the same broken results.

This model was already showing cracks before AI started reshaping how answers get surfaced online, which is why my approach has been to put SEO into the product so the SEO team has access to internal levers.

User empathy is required

The next era of search will not reward people who are solely focused on managing workflows or keeping stakeholders informed about prompt visibility. Growth will come, as it always should, from people who understand what search users are actually trying to accomplish when they type a query or ask an AI assistant a question, and how a product's architecture can either support or destroy that intent at scale.

That is not a traditional marketing skill, nor is it purely a technical skill in the way most SEO practitioners use that word. As before, this is a product skill, specifically the kind of deep, user-obsessed, systems-aware product thinking that gets applied to the question of how search engines and AI models decide which answers deserve to be seen.

This person looks more like a product manager than anything else, and not a marketing engineer or a content strategist who has picked up a few technical certifications along the way. What I would actually look for in that person is a specific combination of capabilities that I have rarely seen packaged together in a single job description, but that I have consistently seen in the SEO managers who produced outsized results.

SEO managers are product managers

Let’s call this an SEO product manager, as I have argued many times in this weekly newsletter. This PM has to understand what a user means when they search, not just the words they type, and that requires genuine curiosity about people and problems rather than proficiency in a research methodology. The query is the user raising their hand to ask for something they need solved, and the job is to understand the problem well enough to build something that a search engine or AI model trusts enough to cite. The managers I have worked with who had this quality never needed to be told to think about the user first.

Naturally, we can’t just have a PM building something without also understanding SEO. This PM needs an intuitive understanding of how search engines and AI models reason about relevance, which goes beyond conventional technical SEO. An SEO product manager has a mental model of how Google and the LLMs that increasingly surface answers assess whether a source is authoritative.

The PM understands the reasoning behind the algorithm, not just the outputs of the tools that measure it. They intuitively know how topical depth signals expertise and how a product's architecture conveys meaningful information to a crawler about the organization behind it. This goes so much beyond just spouting off Domain Authority calculations.

Data understanding is a requirement

Many SEO managers I meet have no idea how to pull their own data, and frankly, with AI, there’s no excuse for that today. An SEO manager might not have access to all data, but they should be able to use and manipulate the internal data they do have. Sharing a report from an external SEO tool is not excusable. The manager needs to be able to sift through sometimes messy data to form a hypothesis. This is a different cognitive task than sending out a weekly update.

They should be able to look at a GSC export and see a strategic story in it, connect crawl data to business metrics in a way that makes an engineering team care about fixing something they would otherwise deprioritize.

Technical skills

Technical skills have always been a key component of SEO teams, but with AI, they are becoming much less important. Whereas in the past an SEO manager might have needed to read source code and even recommend code fixes, AI can handle this. This means that soft skills become the most important skill in today’s SEO work.

The SEO product manager has to be able to operate credibly in all those conversations, build trust with people with different incentives, and move work forward through relationships rather than org-chart positions. Soft skills are where many otherwise talented SEO practitioners fail, because the skill required is fundamentally political in the best sense of that word: the ability to understand what other people care about and to connect your priorities to their goals.

Check out this fantastic interviewing guide from Nick Leroy.

AI utilization is required

It should go without saying, but any SEO PM can use AI as a genuine force multiplier without surrendering the judgment that makes the work worth doing. AI can generate content variations, run site audits, surface patterns in crawl data, monitor how LLMs are citing competitors, and accelerate almost every repeatable task in the SEO workflow. What it cannot do is decide what matters.

Those calls require accumulated experience and the kind of business judgment that only develops through doing the work with real stakes attached. The SEO product manager uses AI to move faster and cover more surface area, while remaining the person who decides where to point all that capability. Handing the judgment over to the tool is the fastest way to produce a lot of confident, well-formatted work that leads nowhere.

Many SEO and AEO JDs look like past JDs but use AI-driven language. Today’s JDs need a solid update (paid subscribers can use the attached template). The job needs an upgrade that captures these skill sets and doesn’t just swap keyword-ranking reports for prompt rankings. You need someone who can walk into a product review and understand what is being built and why. This is a person who can make their own roadmap of what should be built and defend it.

The best SEO managers I have worked with already operate this way, even if their titles never reflected it and their org charts gave them no formal authority to do so. Some of them are on the job market because their companies mistakenly thought AI transformations meant they didn’t need SEO at all. These people are available, and if you are ready to take the leap to real growth from AEO, I am happy to make introductions. Just reply to this email.

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