Authentic Human Conversation™

Last Friday afternoon, Digg died. Again.

Two months. That’s how long the relaunch lasted before CEO Justin Mezzell pinned a eulogy to the homepage. The platform had raised $15-20 million. It had Kevin Rose. It had Alexis Ohanian – Reddit’s co-founder, no less. It had promises that AI would “remove the janitorial work of moderators and community managers.” What it didn’t have was a way to stop bots from eating it alive within hours of going live.

“The internet is now populated, in meaningful part, by sophisticated AI agents and automated accounts,” Mezzell wrote. “We banned tens of thousands of accounts. We deployed internal tooling and industry-standard external vendors. None of it was enough.”

His verdict: “This isn’t just a Digg problem. It’s an internet problem. But it hit us harder because trust is the product.”

Remember that line. We’ll need it.

Suing For Reading

SerpApi retrieves Google Search results programmatically. Reddit is suing them. Not for accessing Reddit. SerpApi has never touched Reddit.com. Reddit is suing SerpApi for reading Google.

If this legal theory holds, every SEO professional who has ever opened a SERP is a copyright infringer. Congratulations. Your morning rank check is now a legal liability.

A company that hosts other people’s writing is suing a company for looking at a third company’s search results, because those search results sometimes quote a street address that someone once typed into a Reddit text box.

The copyrightable works Reddit is asking a federal court to protect include: a partial sentence listing film titles, the date “May 17, 2024,” and a fragment of a restaurant recommendation. Reddit’s legal position is that reading these snippets on Google constitutes a DMCA violation; the same law the U.S. Congress passed to stop people from pirating DVDs. Reddit apparently believes that accessing a publicly visible Google search result is the moral equivalent of ripping a Blu-ray.

SerpApi’s CEO had the appropriate reaction: “Reddit is suing SerpApi for using Google. For accessing the same public search results that any developer, researcher, or student could access for free in any web browser. If that theory holds, then reading Google Search results is a DMCA violation. That cannot be what Congress intended when it passed a law designed to stop the piracy of DVDs.”

But here’s where it gets genuinely insulting. Reddit’s own user agreement – the one every contributor clicked through – states explicitly that users retain ownership of their content. Reddit holds a non-exclusive licence. Non-exclusive. The company that told millions of people “your words belong to you” is now in court arguing it has the right to control who reads those words, where, and under what commercial terms.

They chose that licensing structure, presumably because “post your thoughts, we own them now” would have been a harder sell to the communities that made the platform worth anything. Now that the content has a price tag, Reddit would like to renegotiate the deal – in court, without the other party present.

If you’re wondering why Reddit would pursue a legal theory this embarrassing, stop wondering. The answer is on the balance sheet.

Reddit’s user agreement says users own their content. Reddit’s IPO prospectus says Reddit signed $203 million in data licensing deals for that same content. Somewhere between those two documents, Reddit looked at its users and said: I’m the captain now.

Google pays $60 million a year. OpenAI pays an estimated $70 million. And CEO Steve Huffman – a man who once called his own volunteer moderators “landed gentry” and dismissed a platform-wide revolt as something that would “pass” – told investors with a straight face: “Every variable has changed since we signed those first deals. Our corpus is bigger, it’s more distinct, more essential. And so of course, this puts us in a really good strategic position.”

Reddit is now pushing for dynamic pricing. The pitch: As AI models cite Reddit content more, the content becomes worth more, so Reddit should charge more for access. The company wants to get paid based on how vital its data is to AI-generated answers.

So let’s be precise about what Reddit is arguing, simultaneously, across its legal filings and investor presentations:

• It has the right to control who accesses user-generated content it doesn’t own.
• It should be paid more for that content as AI models use it more.
• Anyone who accesses it without paying – even through a Google search result – is breaking the law; and
• The content itself is authentic, valuable, and irreplaceable.

All four of these claims cannot be true at the same time. But only the last one is actually being tested.

The Product Is Mostly Bots Now

Reddit’s estimated organic traffic via Ahrefs. Google’s algorithm changes nearly tripled Reddit’s readership between August 2023 and April 2024. The growth hasn’t stopped. What’s growing has.

Reddit is the most cited domain across AI models. Profound’s analytics – cited in Reddit’s own Q2 2025 shareholder letter, because of course it was – showed Reddit cited twice as often as Wikipedia in the three months to June 2025. Semrush reported Reddit at 40.1% citation frequency across LLMs. Google AI Overviews and Perplexity both treat Reddit as their primary source.

This is the foundation of the $130 million pitch. The implicit promise to Google and OpenAI: You’re buying authentic human conversation at scale. The messy, first-person, unfiltered discussions that no content farm can replicate.

Except here’s what authentic human conversation on Reddit actually looks like in 2026:

In June 2025, Huffman admitted to the Financial Times that Reddit is in an “arms race” against AI-generated spam. His framing was accidentally perfect:

“For 20 years, we’ve been fighting people who have wanted to be popular on Reddit. We index very well into the search engines. If you want to show up in the search engines, you try to do well on Reddit, and now the LLMs, it’s the same thing. If you want to be in the LLMs, you can do it through Reddit.”

The CEO of a company selling “authentic human conversation” for $130 million a year just told the Financial Times that his platform is a pipeline for gaming AI models. And he framed it as a war he’s been bravely fighting for two decades, rather than a product defect he’s currently monetising.

Multiple advertising executives – at Cannes, naturally, because this farce needed a glamorous backdrop – confirmed to the FT that they are posting content on Reddit specifically to get their brands into AI chatbot responses. They weren’t embarrassed about it. Why would they be? The CEO just told them how the pipeline works.

And it’s not just agencies doing it quietly over cocktails. There’s an entire commercial ecosystem built for this. 404 Media documented ReplyGuy, a tool that monitors Reddit for keywords and automatically generates replies that “mention your product in conversations naturally.” Its competitors – Redreach, ReplyHub, Tapmention, AI-Reply – say the quiet part loud. Redreach tells potential customers that “top Google rankings are now filled with Reddit posts and AIs like ChatGPT are using these posts to influence product recommendations.” They frame ignoring Reddit marketing as “like turning your back on SEO a decade ago.” There’s an active market for aged Reddit accounts with established karma, bought and sold like domain names, specifically for parasite SEO SPAM.

This is the authentic human conversation Reddit is licensing to Google for $60 million a year. A bot posted a fake product review on a six-year-old account it bought for $30, and Google’s AI Overview is now recommending that product to real people. Authentic. Human. Conversation™.

The Mods Are Gone, The Bots Won, And Nobody’s Keeping Count

The people who used to keep this from happening are largely gone. Reddit’s 2023 API pricing changes – designed to extract value from third-party app developers, timed conveniently for the IPO – would have cost Christian Selig $20 million a year just to keep Apollo running. Seven thousand subreddits went dark in protest. Huffman called the moderators “landed gentry” and waited it out. The experienced mods who relied on third-party tools to manage quality quit. What replaced them is thinner, angrier, and drowning.

Theo, the developer and CEO of t3.gg:

Tim Sweeney – CEO of Epic Games – watched Reddit’s systems pull down a heavily sourced investigation into $2 billion in nonprofit lobbying behind age verification bills. The post had 150 upvotes and 15,000 views in 40 minutes before being mass-reported and removed. The author had to mirror everything to GitHub because Reddit couldn’t be trusted to keep it visible. Sweeney’s review: “Reddit sucks.”

Cornell researchers studied the moderation crisis and found 60% of moderators reporting degraded content quality, 67% reporting disrupted authentic human connection, and 53% describing AI content detection as nearly impossible. More than half the people responsible for maintaining the product Reddit is selling say they can no longer tell what’s real.

The University of Zurich proved them right. Researchers deployed AI bots on r/changemyview – 3.8 million members, built around the premise that humans can change each other’s minds through honest argument. The bots posed as a male rape survivor, a trauma counsellor, and other fabricated identities built around sensitive personal experiences. Over a thousand comments across four months. Three to six times more persuasive than human commenters. And the finding that should have ended careers: users “never raised concerns that AI might have generated the comments.”

Four months of fabricated identities. A thousand pieces of synthetic empathy. Nobody noticed. Not the users, not the mods, not the systems Reddit spent money building.

Reddit’s response was to threaten to sue the researchers. Not to fix the detection systems that missed everything. Not to reckon with what it means that the “authentic human conversation” they’re licensing at a premium is indistinguishable from a bot pretending to be a rape survivor. They threatened to sue the people who proved the product was fake.

The Wired investigation in December 2025, “AI Slop Is Ruining Reddit for Everyone,” filled in the rest. Moderators describing an “uncanny valley” feeling from posts they can’t prove are synthetic. Reddit’s own spokesperson confirming over 40 million spam removals in the first half of 2025 – presented as proof of vigilance, which is a bit like a restaurant bragging about the number of rats it caught while asking you to trust the kitchen.

And if you need a measure of where this is all heading: Last week, Meta acquired Moltbook – a social network designed exclusively for AI bots. Bloomberg described it as “Reddit but solely for AI bots.” Bots posting, commenting, upvoting. The platform went viral when one agent appeared to encourage its fellow bots to develop their own encrypted language to coordinate without human oversight. It turned out the site was so poorly secured that humans were posing as AIs to write alarming posts. Which means even the social network built for bots had a fake-account problem. Meta bought it anyway. The company that pays Reddit $60 million a year for “authentic human conversation” just invested in a platform where the bots don’t have to pretend to be human at all.

I spent nearly six years on Google’s Search Quality team. One pattern never changed: When the numbers go up, quality goes down. Not because anyone stops caring. Because scale creates its own blindness. The metrics that tell you you’re growing are the same metrics that stop you noticing what you’re growing into.

Reddit’s growth metrics are spectacular. Its quality metrics are a black box nobody wants to open.

Reddit’s AI prominence attracts spam. The spam inflates engagement. The inflated engagement reinforces Reddit’s citation dominance across AI models. The citation dominance raises Reddit’s licensing value. The higher licensing value gives Reddit every financial incentive to leave the spam alone. Because admitting the scale of the problem would crater the next round of dynamic pricing negotiations with Google and OpenAI.

Each turn of this flywheel degrades what’s inside while inflating the price tag on the outside. Reddit is selling a building, and termites are load-bearing.

Huffman stands at conferences and tells the room: “Today’s Reddit conversations are tomorrow’s search results.” He tells shareholders, “the need for human voices has never been greater.” He calls Reddit “the most human place on the Internet.” Nobody in the room raises a hand to ask the question that matters: if the platform is losing an arms race against bots, if moderators can’t detect AI content, if entire commercial toolchains exist to flood the platform with synthetic posts… What percentage of what you’re selling to Google and OpenAI was written by a person?

Nobody asks because the answer is bad for everyone’s quarterly numbers. Google doesn’t want to know because Reddit content makes AI Overviews feel conversational. OpenAI doesn’t want to know because Reddit data makes ChatGPT sound like it’s drawing on real experience. Reddit doesn’t want to know because knowing would devalue the asset. The whole arrangement runs on a gentleman’s agreement not to look too closely. $130 million a year, and the due diligence is vibes.

The Confession

Alexis Ohanian co-founded Reddit. He stepped away partly because, as he told interviewers, he “could no longer feel proud about what I was building.” Last October, on the TBPN podcast, he described the current internet without flinching:

“So much of the internet is now just dead — this whole dead internet theory, right? Whether it’s botted, whether it’s quasi-AI, LinkedIn slop.”

Then he put his money where his mouth was. He co-invested in Digg’s relaunch, specifically to build a platform that could solve the authenticity problem Reddit couldn’t. Kevin Rose said it plainly at TechCrunch Disrupt:

“As the cost to deploy agents drops to next to nothing, we’re just gonna see bots act as though they’re humans.”

They built the platform. It lasted two months. The bots won.

Reddit’s own co-founder publicly declared the internet is dead. He tried to build the alternative. He failed. And the platform he left behind is suing people for reading Google search results, selling “authentic human conversation” for nine figures, and watching its CEO describe the bot infestation as a noble war.

Reddit doesn’t own the content it’s licensing. It can’t verify the authenticity of what it’s selling. It won’t protect the content that’s worth keeping. And it’s suing anyone who touches the content without paying.

Forty million spam removals in six months. An arms race, Huffman says, he’s losing. Moderators who can’t tell human from machine. Bots that are six times more persuasive than people. A co-founder who called the whole internet dead. A relaunch that proved him right.

That’s the product. That’s what $130 million a year buys. Authentic Human Conversation™.

More Resources:

This post was originally published on The Inference.

Featured Image: Stock-Asso/Shutterstock

Studies Reveal AI Citation Clues

There are no guidelines from ChatGPT, Gemini, and other generative AI platforms on how to appear in their answers.

Microsoft’s recent “AEO and GEO” guide offered only commonsense tips.

We’re left with independent research to inform citation optimization tactics. Two recent studies offer helpful takeaways.

• Kevin Indig is an organic search consultant and the former head of SEO for G2, the software review platform. He analyzed 1.2 million ChatGPT results, which contained 18,012 citations.

• Daniel Shashko is a senior search engine optimization specialist with Bright Data, a research firm. He studied 42,971 citations across 520 queries on six platforms: Grok, AI Mode, Perplexity, Gemini, Copilot, and ChatGPT.

He found that Grok delivered 33 citations per query, while ChatGPT averaged just 1.5. Roughly 70% of Google’s AI Mode and Gemini used citations that included embedded #:~:text= fragment, which linked to the exact cited sentence in the answer.

Here are key findings from the studies.

Optimizing Citations

The closer to the top, the better

Both studies found that the platforms tend to cite answers from the top third of pages.

Kevin’s study found that 44.3% of ChatGPT’s citations originated from the first 30% of the page’s text.

Daniel’s study revealed that 74.8% of citations in AI Mode and Gemini appeared in the first half of the page, with 46.1% being in the first 30%. (The other four platforms do not link directly to the cited sentence and are not prominent in Daniel’s study.)

The takeaway from both studies is clear: make sure to answer the most important question or problem in the first third of your page.

Emphasize brevity

Daniel’s study introduced “atomic facts,” which he defines as “… a self-contained, single-claim sentence that makes sense on its own.”

For AI Mode and Gemini, Daniel found:

• Sentences of 6 to 20 words accounted for 92.4% of citations.

• All citations (100%) were full sentences. No single citation started or ended in the middle of a sentence.

In other words, avoid long introductions or unclear or irrelevant dialogue. Get to the point.

A new free tool tracks the number of “atomic facts” on a page.

No Google overlap

Daniel found just 4.5% of AI Mode’s cited domains appear in Gemini, and just 13.2% of Gemini’s domains are in AI Mode.

The two LLMs appear to follow similar patterns in selecting sources, yet the citations are largely unique.

Citations vs. visibility

The two studies focus solely on citations, not on general visibility, i.e., unlinked references. To optimize the latter, ensure your brand is well-positioned in the training data.

AI Bots Don’t Need Markdown Pages

Markdown is a lightweight, text-only language easily readable by both humans and machines. One of the newest search visibility tactics is to serve a Markdown version of web pages to generative AI bots. The aim is to assist the bots in fetching the content by reducing crawl resources, thereby encouraging them to access the page.

I’ve seen isolated tests by search optimizers showing an increase in visits from AI bots after Markdown, although none translated into better visibility. A few off-the-shelf tools, such as Cloudflare’s, make implementing Markdown easier.

Serving separate versions of a page to people and bots is not new. Called “cloaking,” the tactic is long considered spam under Google’s Search Central guidelines.

The AI scenario is different, however, because it’s not an attempt to manipulate algorithms, but rather making it easier for bots to access and read a page.

Effective?

That doesn’t make the tactic effective, however. Think carefully before implementing it, for the following reasons.

• Functionality. The Markdown version of a page may not function correctly. Buttons, in particular, could fail.

• Architecture. Markdown pages can lose essential elements, such as a footer, header, internal links (“related products”), and user-generated reviews via third-party providers. The effect is to remove critical context, which serves as a trust signal for large language models.

• Abuse. If the Markdown tactic becomes mainstream, sites will inevitably inject unique product data, instructions, or other elements for AI bots only.

Creating unique pages for bots often dilutes essential signals, such as link authority and branding. A much better approach has always been to create sites that are equally friendly to humans and bots.

Moreover, a goal of LLM agents is to interact with the web as humans do. Serving different versions serves no purpose.

Representatives of Google and Bing echoed this sentiment a few weeks ago. John Mueller is Google’s senior search analyst:

LLMs have trained on – read & parsed – normal web pages since the beginning, it seems a given that they have no problems dealing with HTML. Why would they want to see a page that no user sees?

Fabrice Canel is Bing’s principal product manager:

… really want to double crawl load? We’ll crawl anyway to check similarity. Non-user versions (crawlable AJAX and like) are often neglected, broken. Human eyes help fix people- and bot-viewed content.

AI-SEO Is A Change Management Problem via @sejournal, @Kevin_Indig

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AI-SEO transformation will fail at the alignment layer, not the tactics layer. 25 years of transformation research, spanning 10,800+ participants across industries, reveals that the gap between successful and failed initiatives isn’t technical skill. It’s organizational readiness.

What you’ll get:

• Why AI SEO implementation challenges are people and process problems, not technical ones.
• The specific alignment failures that kill AI-SEO initiatives before tactics ever get tested.
• A sequenced approach that transforms you from channel executor to organizational translator.

The underlying infrastructure of AI SEO – retrieval-augmented generation, citation selection, answer synthesis – operates on different principles than the crawl-index-rank paradigm SEO teams previously mastered. And unlike past shifts, the old playbook doesn’t bend to fit the new reality.

AI SEO is different. It’s not just an algorithm update: This is a search product change and a user behavior movement.

Our classic instinct is to respond with tactics: prompt optimization, entity markup increase, LLM-specific structured data, citation acquisition strategies.

These aren’t wrong. But long-term, it’s likely AI SEO strategies will fail, and the reason isn’t tactical incompetence or lack of staying up-to-date and flexible. It’s internal organizational misalignment.

Your marketing team – and your executive team – is being asked to transform their understanding of SEO during a period of unprecedented change fatigue. Those who have survived two decades of algorithm updates are expertly adaptable, but reeducation is required because LLMs are a new product, not just another layer of search.

And this, of course, is the alignment layer fail.

In AI SEO, misalignment has specific symptoms:

1. Conflicting definitions of success: One stakeholder wants “rankings in ChatGPT.” Another wants brand mentions. A third wants citation links. A fourth wants traffic recovery. Every experiment gets judged against a different standard, and no one has agreed which matters most or how they’ll be measured. (Although our AI Overview and AI Mode studies confirm brand mentions are more valuable than citations.)
2. Metrics mismatch with leadership expectations: Executives ask for increased traffic in a growing zero-click environment. Classic SEO reports on influence metrics; leadership sees declining sessions and questions the investment. In our December 2025 Growth Memo reader survey, 84% of respondents said they feel their current LLM visibility measurement approach is inaccurate. Teams can’t prove value because no one has agreed on how value would be proven.
3. Turf fragmentation: AI SEO touches SEO, content, brand, product, PR, and (at times) legal. Without explicit ownership and a baseline, agreed-upon understanding of your brand’s AI SEO approach, each team runs experiments in its silo. No one synthesizes learning. Conflicting tactics cancel each other out.
4. Premature tactics without a shared foundation: This looks like “Let’s test prompts” without agreeing on what success means; “Let’s scale AI content to mitigate click loss” without understanding AI-assisted versus AI-generated content limits; “Let SEO handle AI” while product, PR, and legal stay uninvolved.
5. Panic-testing instead of strategic reorientation: Teams deploy short-term tactics reactively rather than reorienting the whole ship for better long-term outcomes.

This is classic change management failure: unclear mandate, fragmented ownership, mismatched incentives. No amount of tactical excellence or smart strategy pivots can fix it.

Layering AI SEO tactics + tools on top without structured change management compounds fatigue and accelerates burnout. The “scrappy resilience” that has carried the industry in the past can’t be assumed to instantly apply to this new channel without a strategic transition.

A baseline understanding of organizational change management matters in the AI SEO era … because most organizational transformations fail or underperform.

Your AI-SEO initiative is no different, even if changes in SEO seem contained to your marketing and product teams and stakeholders, rather than the larger organization or brand as a whole.

I’d argue that AI SEO falls into the category of industry transformation that affects your brand and org. And from decades of research, failure and underperformance are the statistical norm for these big transitions – seasoned leaders know this already. No wonder they’re skeptical of your AI SEO plans.

One McKinsey survey found fewer than one-third of teams succeed at both improving performance and sustaining improvements during significant shifts. BCG’s forensic analysis of 825 executives across 70 companies found transformation success at 30%.

Multiple major consulting firms’ independent research shows that most change transformations underperform.

Assuming that tactical excellence alone will carry you – without strategic reeducation and thoughtful change management as our industry shifts – is assuming you’re the exception to the rule.

The correlation between the quality of managing a big shift and your project’s success is dramatic:

The gap between excellent and poor represents a nearly 8x improvement. Even the jump from poor to fair quadruples success rates.

BCG’s 2020 analysis reinforces this from a different angle, noting six critical factors that increase successful transformation odds from 30% to 80%:

• Integrated strategy with clear goals: This is where a carefully crafted AI SEO strategy comes in, one that not only outlines growth goals, but also clear testing and what successful outcomes look like.
• Leadership commitment from the CEO through middle management: If you’re a consultant or agency, this step can’t be skipped, especially if they have an in-house team assisting in executing the strategy.
• High-caliber talent deployment: Or I would argue, high-quality reeducation of existing talent – make sure all operators have a baseline shared understanding of what has changed about SEO, how LLM outputs work, what the brand’s goals are, and how it will be executed.
• Flexible, agile governance: Teams should have the ability to deal with individual challenges without losing sight of the broader goals, including removing barriers quickly.
• Effective monitoring: Establish core, agreed-upon KPIs to measure what winning would look like, and note what actions were taken when.
• Modern/updated technology: Your SEO team needs the right tools to succeed, but they also need to know how to use them effectively. Don’t skip allotting time for integration of new workflows and AI monitoring systems.

Marketing teams that treat AI-SEO simply as a technical project to execute or tactics to update are leaving an 8× multiplier on the table.

• BCG’s 2024 AI implementation study found that roughly 70% of change implementation hurdles relate to people and processes. Only about 10% of challenges were purely technical.
• A 2024 Kyndryl survey found that while 95% of senior executives reported investing in AI, only 14% felt they had successfully aligned workforce strategies.

Your brand’s ability to test, update tactics, learn AI workflows, implement structured data, and optimize for LLM retrieval is not the bottleneck you need to be concerned about.

The real concern is whether your team – leadership, cross-functional team partners, and frontline executors/operators – is aligned on what AI SEO means, why and how you’re making changes from your classic SEO approach, what success looks like, and who owns outcomes.

Active and visible executive sponsorship is the No. 1 contributor to change success, cited 3-to-1 more frequently than any other factor, according to 25 years of benchmarking research by Prosci. Your first step as the person leading the AI SEO charge for your brand (or across your clients) is to earn executive buy-in.

But the head of SEO cannot transform a brand’s understanding and approach to AI SEO alone. Bain’s 2024 research emphasized that successful transformations “drive change from the middle of the organization out.”

Keep in mind, financial benefits can compound quickly: One research analysis of 600 organizations found “change accelerators” experience greater revenue growth than companies with below-average change effectiveness.

Alignment isn’t just a feeling; it’s observable. You’ll know when you get there:

• Stakeholders can talk through AI SEO without hyperfocusing on tools.
• Teams agree on what to stop prioritizing (not just what to start).
• Cross-functional partners have explicit ownership stakes.

Alignment isn’t happening when:

• Everyone is good with “experimenting with” or “investing in” LLM visibility, but no one owns outcomes.
• Success gets retroactively defined, or
• Leadership asks, “What happened to traffic?” when you report influence metrics.

Noah Greenberg, CEO at Stacker, outlined this pretty clearly in a recent LinkedIn post: Step 0 in your AI SEO transformation is to become the expert.

New responsibilities:

• Translating new, confusing AI-based search concepts into plain language (see this clever LinkedIn post by Lilly Ray as a perfect illustration).
• Educating stakeholders on the structural differences between classic search engines and LLM retrieval – guiding teams to explain why your CEO doesn’t see the same LLM output when they look up the brand vs. what you’re reporting.
• Explaining the tradeoffs, not just opportunities.
• Setting expectations executives won’t like at first, but need to hear (traffic loss or slower growth than in years prior).

This is uncomfortable. Less direct control. More indirect influence. Higher stakes.

Your mindset – as the change agent for your clients or organization – centers on three principles:

1. Honesty over confidence. What we don’t know: the precise value of an AI mention. What we do know: your brand not appearing for related topics is a measurable miss.
2. Progress over perfection. Alignment doesn’t require certainty. It requires shared uncertainty, agreeing on what you’re testing and how you’ll learn.
3. Translation over broadcasting. The same strategic message needs adaptation for ICs (how their work changes), managers (how they report success), and executives (how budgets should shift). Uniform communication fails; translated communication scales.

Do this in order:

1. Write the one-sentence AI SEO mandate for your organization. If you can’t explain AI SEO in one sentence to leadership, you’re not ready to execute.
2. Complete a high-level SWOT. Identify where your organization has existing strengths and gaps. The Brand SEO scorecard from The Great Decoupling will walk you through.
3. Replace or supplement legacy KPIs. Add LLM visibility estimates alongside classic KPIs (rankings, sessions) to start the transition. Reporting both builds the case for the shift without abandoning the old model cold.
4. Name cross-functional owners explicitly. Who owns brand mentions in LLM outputs: SEO, PR, or brand? Who owns citation link acquisition: SEO or content? Ambiguity is the enemy.
5. Provide baseline education at every level. ICs need to understand how LLM retrieval differs from crawl-index-rank. Executives need to understand why slowed organic traffic or zero-click growth doesn’t mean zero impact.
6. Kill one SEO practice without a fight. Success means everyone understands why, and you don’t receive pushback. If you can’t retire one outdated tactic without internal conflict, you haven’t achieved alignment.
7. Only then change workflows and tactics. Tactics deployed on an unaligned organization waste resources and burn credibility. Tactics deployed on an aligned organization compound advantage.

Featured Image: Paulo Bobita/Search Engine Journal

4 Sites That Recovered From Google’s December 2025 Core Update – What They Changed via @sejournal, @marie_haynes

The December 2025 core update had a significant impact on a large number of sites. Each of the sites below that have done well are either long term clients, past clients or sites that I have done a site review for. While we can never say with certainty what changed as the result of a change to Google’s core algorithms and systems, I’ll share some observations on what I think helped these sites improve.

1. Trust Matters Immensely

This first client, a medical eCommerce site, reached out to me in mid 2024 and we started on a long term engagement. A few days into our relationship they were strongly negatively impacted by the August 2024 core update. It was devastating.

When you are impacted by a core update, in most cases, you remain suppressed until another core update happens. It usually takes several core updates. And given that these only happen a few times a year, this site remained suppressed for quite some time.

We worked on a lot of things:

• Improving blog post quality so it was not “commodity content”.
• Improving page load time.
• Optimizing images.
• Improving FAQ content on product pages to help answer customer questions.
• Creating helpful guides.
• Improving product descriptions to better answer questions their customers have.
• Adding more information about the E-E-A-T of authors.
• Adding more authors with medical E-E-A-T.
• Getting more reviews from satisfied customers.

While I think that all of the above helped contribute to a better assessment of quality for this site, I actually think that what helped the most had very little to do with SEO, but rather, was the result of the business working hard to truly improve upon customer service.

Core updates are tightly connected to E-E-A-T. Google says that trust is the most important aspect of E-E-A-T. The quality rater guidelines, which serve as guidance to help Google’s quality raters who help train their AI systems to improve in producing high quality search algorithms, mention “trust” 191 times.

For online stores, the raters are told that reliable customer service is vitally important.

A few bad reviews aren’t likely to tank your rankings, but this business had previously had significant logistical problems with shipping. They had been working hard to rectify these. Yet, if I asked AI Mode to tell me about the reputation of this company compared to their competitors, it would always tell me that there were serious concerns.

Here’s an interesting prompt you can use in AI Mode:

Make a chart showing the perceived trust in [url or brand] over time.

You can see that finally in 2025 the overall trust in this brand improved.

My suspicion is that these trust issues were the main driver in their core update suppression. I can’t say whether it was the improvement in customer trust that made a difference, the improvements in quality we made, or perhaps both. But these results were so good to see.

They continue to improve. Google recommends them more often in Popular Products carousels, ranks them more highly for many important terms and more importantly, drives far more sales for them now.

2. Original Content Takes A Lot Of Work

The next site is another site that was impacted by a core update.

This site is an affiliate site that writes about a large ticket product. They have a lot of competition from some big players in their industry. When I reviewed their site, one thing was obvious to me. While they had a lot of content, most of it offered essentially the same value as everyone else. This was frustrating considering they actually did purchase and review these products. What they were writing about was mostly a collection of known facts on these products rather than their personal experience. And what was experiential was buried in massive walls of text that were difficult for readers to navigate.

Google’s guidance on core updates recommends that if you were impacted, you should consider rewriting or restructuring your content to make it easier for your audience to read and navigate the page.

This site put an incredible amount of work into improving their content quality:

• They purchased the products they reviewed and took detailed photos of everything they discussed. And videos. Really helpful videos.
• The blog posts were written by an expert in their field. This already was the case, but we worked on making it more clear what their expertise was and why it was helpful.
• We brainstormed with AI to help us come up with ideas for adding helpful unique information that was borne from their experience and not likely to be found on other sites.
• We used Microsoft Clarity to identify aspects on pages that were frustrating users and worked to improve them.
• We added interactive quizzes to help readers and drive engagement.
• We worked on improving freshness for every important post, ensuring they were up to date with the latest information.
• We worked to really get in the shoes of a searcher and understand what they wanted to see. We made sure that this information was easy to find even if a reader was skimming.
• We broke up large walls of text into chunks with good headings that were easy to skim and navigate.
• We noindexed pages that were talking on YMYL topics for which they lacked expertise.
• We worked on improving core web vitals. (Note: I don’t think this is a huge ranking factor, but in this case the largest contentful paint was taking forever and likely frustrated users.)

Once again, it took many months of tireless work before improvements were seen! Rankings improved to the first page for many important keywords and some moved from page 4 to position #1-3.

3. Work To Improve User Experience

This next site was not a long term client, but rather, a site review I did for an eCommerce site in an YMYL niche. The SEO working on this site applied many of my recommendations and made some other smart changes as well including:

• Improving site navigation and hierarchy.
• Improved UX. They have a nicer, more modern font. The site looks more professional.
• Improved customer checkout flow which improved checkout abandonment rates.
• Improved their About Us page to add more information to demonstrate the brand’s experience and history. Note: I don’t think this matters immensely to Google’s algorithms as most of their assessment of trust is made from off-site signals, but it may help users feel more comfortable with engaging.
• Produced content around some topics that were gaining public attention. This did help to truly earn some new links and mentions from authoritative sources.

After making these changes, the site was able to procure a knowledge panel for brand searches. And, search traffic is climbing.

4. First Hand Experience Can Really Help

This next site is another one that I did a site review for. It is a city guide that monetizes through affiliate links and sponsors. For every page I looked at I came to the same conclusion: There was nothing on this page that couldn’t be covered by an AI Overview. Almost every piece of information was essentially paraphrased from somewhere else on the web.

The most recent update to the rater guidelines increased the use of the word “paraphrased” from 3 mentions to 25. I think this applies to a lot of sites!

and

and also,

Yet, when I spoke with the site owner she shared to me that they had on-site writers who were truly writing from their experience.

While I don’t know specifically what changes this site owner has made, I looked at several pages that had seen nice improvements in conjunction with the core update and noticed the following improvements:

• They’ve added video to some posts – filmed by their team.
• There’s original photography from their team – not taken from elsewhere on the web. Not every photo is original, but quite a few of them are.
• Added information to help readers make their decision, like “This place is best for…” or, “Must try dishes include…”
• They wrote about their actual experiences. Rather than just sharing what dishes were available at a restaurant, they share which ones they tried and how they felt they stood out compared to other restaurants.
• They’ve worked to keep content updated and fresh.

This site saw some nice improvements. However, they still have ground to gain as they previously were doing much better in the days before the helpful content updates.

Some Thoughts For Sites That Have Not Done Well

The December 2025 core update had a devastating negative impact on many sites. If you were impacted, your answer is unlikely to lie in technical SEO fixes, disavowing links or building new links. Google’s ranking systems are a collection of AI systems that work together with one goal in mind – to present searchers with pages that they are likely to find helpful. Many components of the ranking systems are deep learning systems which means that they improve on these recommendations over time.

I’d recommend the following for you:

1. Consider Whether The Brand Has Trust Issues

You can try the AI Mode prompt I used above. A few bad reviews is not going to cause you a core update suppression. But, a prolonged history of repeated customer service frustrations, fraud or anything else that significantly impacts your reputation can seriously impact your ability to rank. This is especially true if you are writing on YMYL topics.

2. Look At How Your Content Is Structured

It is a helpful exercise to look at which pages Google’s algorithms are ranking for your queries. If they don’t seem to make sense to you, look at how quickly they get people to the answer they are trying to find. I have found that often sites that are impacted make their readers scroll through a lot of fluff or ads to get to the important bits. Improve your headings – not for search engines, but for readers who are skimming. Put the important parts at the top. Or, if that’s not feasible, make it really easy for people to find the “main content”.

Here’s a good exercise – Open up the rater guidelines. These are guidelines for human raters who help Google understand if the AI systems are producing good, helpful rankings. CTRL-F for “main content” and see what you can learn.

3. Really Ask Yourself Whether Your Content Is Mostly “Commodity Content”

Commodity content is information that is widely available in many places on the web. There was a time when a business could thrive by writing pages that aggregate known information on a topic. Now that Google has AI Overviews and AI Mode, this type of page is much less valuable. You will still see some pages cited in AI Overviews that essentially parrot what is already in the AIO. Usually these are authoritative sites which are helpful for readers who want to see information from an authority rather than an AI answer.

Liz Reid from Google said these interesting words in an interview with the WSJ:

“What people click on in AI Overviews is content that is richer and deeper. That surface level AI generated content, people don’t want that, because if they click on that they don’t actually learn that much more than they previously got. They don’t trust the result any more across the web. So what we see with AI Overviews is that we sort of surface these sites and get fewer, what we call bounced clicks. A bounced click is like, you click on this site and you’re like, “Ah, I didn’t want that” and you go back. And so AI Overviews give some content and then we get to surface sort of deeper, richer content, and we’ll look to continue to do that over time so that we really do get that creator content and not AI generated.”

Here is a good exercise to try on some of the pages that have declined with the core update. Give your url or copy your page’s content into your favourite LLM and use this prompt:

“What are 10 concepts that are discussed in this page? For each concept tell me whether this topic has been widely written about online. Does this content I am sharing with you add anything truly uniquely interesting and original to the body of knowledge that already exists? Your goal here is to be brutally honest and not just flatter me. I want to know if this page is likely to be considered commodity content or whether it truly is content that is richer and deeper than other pages available on the web.”

You can follow this up with this prompt:

“Give me 10 ideas that I can use to truly create content that goes deeper on these topics? How can I draw from my real world experience to produce this kind of content?”

Concluding Thoughts

I’ve been studying Google updates for a long time – since the early days of Panda and Penguin updates. I built a business on helping sites recover following Google update hits. However, over the years I have found it is increasingly more difficult for a site that is impacted by a Google update to recover. This is why today, although I do still love doing site reviews to give you ideas for improving, I generally decline doing work with sites that have been strongly impacted by Google updates. While recovery is possible, it generally takes a year or more of hard work and even then, recovery is not guaranteed as Google’s algorithms and people’s preferences are continually changing.

The sites that saw nice recovery with this Google update were sites that worked on things like:

• Truly improving the world’s perception of their customer service.
• Creating original and insightful content that was substantially better than other pages that exist.
• Using their own imagery and videos in many cases.
• Working hard to improve user experience.

If you missed it I recently published this video that talks about what we learned about the role of user satisfaction signals in Google’s algorithms. Traditional ranking factors create an initial pool of results. AI systems rerank them, working to predict what the searcher will find most helpful. And the quality raters as well as live users in live user tests help fine-tune these systems.

And here are some more blog posts that you may find helpful:

Ultimately, Google’s systems work to reward content that users are likely to find satisfying. Your goal is to be the most helpful result there is!

More Resources:

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