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There is an SEO conversation that I have way too frequently with potential consulting opportunities. It goes something like this: a leader (CEO/CMO/Director) believes their website should be number one for “best CMS,” “WordPress vs Contently,” “top email tool,” or “SurveyMonkey alternative,” and they are reaching out to consultants to find out what’s broken and when they will achieve this “ranking” goal.

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They request audits, backlink research, page speed analysis, and McKinsey-level assessments. In many cases, their current agency already audited their site and recommended fixes, but nothing happened. It is the agency’s fault, of course.

Newsflash, it’s not a technical issue

Ranking for brand comparison and best-of keywords is not a technical SEO challenge. The pages that rank at the top of those queries are not there because someone nailed their URL structure and schema. (I have seen agencies recommend speed as the fix, and that’s even more atrociously ridiculous than schema.) The top-ranking URLs are there because the underlying facts about their product are well-known, widely cited, and repeatedly validated by other sites. You can have the best product on the internet and still get destroyed on “best AI detector” by a competitor whose product is just talked about more, not just linked more.

This is a conversation that most internal SEO teams and agencies need to have when these requests come in. I find that too often in the SEO industry, agencies or in-house teams oblige leaders’ requests without pushing back. One notable example right now is how many SEO managers are signing on to AEO tools they don’t believe in because leadership insists they need one yesterday.

Brand matters more than technical

For these types of queries, which are really brand-type queries, the most important factor is the "fit” of the brand. This comes from reputation, which requires building something worth talking about and then making sure the right people talk about it, and those two things happen in different departments with different budgets and different timelines. (See my posts on the differences between SEO and AEO)

The mechanics of why this is true matter. When someone searches “monday.com vs Asana,” Google is not trying to show a page whose title tag includes both brand names. Instead, they want to be as helpful as possible for the person making a real software decision, who would find the answers most trustworthy and useful.

The ranking signals that determine trustworthiness are almost entirely downstream of reputation: who links to you, how often you get mentioned in editorial contexts, what comparison sites and review platforms say about you, and what real journalists write when they cover your category. None of these signals is impacted in the slightest by technical SEO.

These pages still matter even as AI Overviews expand, because a buyer genuinely deciding between two products is not going to trust a summary from a search engine. They want the full picture, and they WILL click through to find it.

Use PR

Instead, what does work for these kinds of queries is a general PR-type effort. Not the press release version of PR, where you announce a funding round and hope a tech journalist writes it up. What is needed is actual strategic communications work, where you actively seed the facts about your product in the places that matter for your category. That means getting your real differentiators into third-party reviews and having customers talk about you on social media. All social media counts, not just Reddit. Don’t forget that YouTube is a feeder for Google. (Reply for personalized recommendations on how to do this.)

The frustrating part is that most companies treat brand awareness efforts as parallel but separate tracks. The SEO team is promoting technical ideas while the PR team is pitching stories. They need to work together, not just on AEO, where I think the brand team should own it, but on SEO too.

But there is one more thing before we even get to PR.

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Someone has to write the content.

This sounds obvious, but shockingly, I see it missed all the time. A company recently asked me why they aren’t ranking on “best [abc] AI tool,” and I showed them that when I did a site search for the words they wanted, they had never used them on their website. This same company wanted to know why their page didn’t show up on Google when searching for them, unlike the competitor's page. This was an easy answer, too. They had never created that page.

Even when the page is written, it has to be created in a specific way that most companies don’t bother to do. They are writing marketing copy pretending to be an editorial comparison. As in the listicle strategy, which many are gaming for AEO, they are writing “X vs Y” pages that exist to declare themselves the winner in every category, with no acknowledgment that their product has any tradeoffs at all. Sophisticated buyers see through this immediately, so naturally, AI that imitates human thought will do the same.

Pages that should consistently rank for these queries share an honest approach that is uncomfortable for most marketing teams to execute. They outline scenarios in which a competitor is actually the better choice, with specific, concrete reasons why someone would pick one product over another, grounded in actual product behavior rather than positioning language.

Think about what that actually requires internally, and you can see why it would give marketers some angst. It needs a product marketing team willing to document its own weaknesses, and a content team with enough autonomy to publish something that doesn't read like a sales deck. Most companies cannot clear all those bars, which is exactly why supposedly non-biased media sites own these results in most categories. Users trust them because they have no stake in the outcome, and search engines have learned to mirror that trust.

Pages need to be updated to maintain their visibility

There is a genuine problem for SEO teams tasked with winning these queries: The team can build the page, but can’t win that query if they don’t deserve it.

This will be true even when you optimize it technically and even EARN (not buy) some links to it. The truth is that building a winning page is a product problem, not a keyword problem.

These pages, when they win, also need to be consistently updated. You cannot build a comparison page today, spend six months earning the brand mentions and review site citations, and then go back and update the content. By the time your reputation signals are strong enough to compete, the content has gone stale. The content and the off-page work have to move in parallel, which means someone has to be coordinating them, which means this needs to be someone’s actual job and not a side project for SEO.

If you want to rank as the best at whatever or have an honest comparison, you first need to write the content. And then you need to actually earn it.

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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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Every CEO I know has done the same thing in the last two years. They opened ChatGPT, typed in their company name, didn’t like what came back, and then emailed the SEO team or agency to fix it. For the leaders I have had this conversation with, I have been able to redirect their efforts. This post is for everyone else.

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That instant reaction makes sense on the surface. SEO is about visibility in search, LLMs are the new search, voila, the SEO team owns the problem. The logic checks out. It is also completely wrong, and this thinking risks making things worse.

Marketing has always owned SEO

This isn’t just an AI issue; it begins with putting SEO in a marketing org. One of the many reasons a company leaves its SEO potential unfulfilled is that it inadvertently silos the person responsible for SEO, leaving the SEO manager as a marketing individual contributor who must go through their marketing lead to get anything done.

The marketing lead then needs to negotiate for bandwidth on the product and engineering teams to get anything done. This organizational placement about where SEO even sits, especially at a time when the industry is being rewritten, pollutes every resourcing decision and budget conversation.

The organizational structure of SEO as marketing leaves the team without the authority to get things done. An SEO team that can write code has always been rare. Therefore, the best an SEO team can do is make requests of other teams, and those requests are not requirements.

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• Paid subscribers can download my THRICE prioritization template here.

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• Paid subscribers can download my THRICE prioritization template here.

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• Paid subscribers can use this brand visibility checklist to assess if they are hitting the right notes for LLM visibility

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The comparison between SEO and AEO is a trap. It’s easy to look at both and see an LLM response as search results of 2026, but that logic is wrong, and this flawed reasoning is why so many are currently optimizing for a user journey that does not exist in an AI-first world.

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Rankings don’t exist in LLMs

You cannot swap your search rankings for visibility or share of voice in an LLM because the mechanics of the user’s experience have fundamentally changed. This is not an algorithm update that requires a minor tweak in how you structure reporting dashboards from ranking to prompt visibility.

Instead of positioning in search results for a specific keyword, the search UI has shifted to a disaggregated presence across prompts you can never predict or monitor. In short, there is no list of keywords to rank for. There is no page one because the surface area of visibility is now infinite. In an AI response, the click is no longer the desired KPI; therefore, the conversion funnel and SEO strategy built around it have lost their front door.

SEO was always about search engine visibility NOT rankings. Every technical optimization, keyword, and internal link was designed to encourage the Google algorithm to place a URL in the results, thereby initiating a conversion funnel. AEO collapses that model completely.

When an LLM synthesizes ideas it has scraped from around the web into a direct answer, the user gets what they need without ever visiting a site: content is being used to answer questions customers are asking, and most sites will never see a session in analytics for it. The visibility might still happen, but it doesn’t mean anything if the user’s needs have been met.

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When you walk into a meeting and say, “I would really like to do this particular project, but it didn’t score as well as YOUR project in our THRICE framework,” you are banking political capital and showing that you are a team player.

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• Paid subscribers can download this checklist to ensure that their website is customer-centric and has a higher likelihood of being cited by LLMs

• The value of prompt tracking is declining with Google’s personalization in AI mode. Read this post from a few months ago (free for all reade…

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Reddit is not a loophole for AI visibility. The brands that treat it like one are about to find out the hard way, and the communities there will make sure the lesson is public.

Reddit has served as a source of traffic and social media for more than twenty years, but some have only discovered it because they realized that Reddit threads are showing up in LLM responses. Sometimes those threads are cited directly, and other times there is a link to the thread itself.

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The instinct to manufacture content there is understandable. If Reddit is feeding the LLMs, then getting your brand into Reddit conversations looks like a direct distribution channel. This seems like the easiest SEO strategy ever. No budget or strategy required, just seed some positive mentions into the right subreddits and let the models vacuum it up. It sounds almost too clean.

If it sounds too good to be true, it probably is

What happens next is where most of these companies are going to make a mistake that is difficult and slow to recover from. The reason Reddit became a source for LLM training data in the first place is that it accumulated decades of genuine human conversation across thousands of niche communities. Real people with actual emotion, passionately arguing and sharing opinions, became a massive repository of knowledge.

This authenticity is what the models ingested, and it is what makes the signal good enough to influence AI outputs. The value of Reddit as a source did not come from templated press releases or brand messaging.

When brands show up trying to manufacture that signal by seeding fake discussions, hiring agencies to flood relevant subreddits with positive mentions, they are not replicating what made Reddit valuable. These human or AI spam machines are producing something qualitatively different in a way that will become increasingly obvious to the AI systems they are trying to influence. Humans already take one look at this content and know it’s fake, so the AI systems will eventually do the exact same. This brings us to the humans in the mix.

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