In the conversation, Danny Sullivan jokes about how many acronyms have appeared around search and AI, from generative engine optimization to answer engine optimization and AIO. He explains that despite all these new labels, they are essentially subsets of the broader SEO practice. SEO remains the umbrella term for improving content so that people can find it, regardless of whether results appear as blue links, AI answers, or other formats.
He defines SEO as understanding how people seek information, how that information is presented, and then making sure you do the right things to be successful in those environments. That can include showing up in voice answers or AI-powered results, not just traditional web listings. New formats like AEO or GEO are framed as specializations within SEO, similar to local SEO, where there may be format-specific considerations but the foundation is still the same discipline.
Google’s North Star Rewarding Helpful, Human‑First Content
Google’s ranking systems are designed around a clear north star: rewarding content that is great for people and written for human beings rather than for algorithms or large language models. The goal is to surface pages that leave users feeling satisfied, saying “that was what I was looking for, that’s what I needed.” When creators already focus on this kind of content, they are naturally positioned to do well as formats evolve.
The more site owners try to optimize for a specific system or short‑term opportunity, the more they risk drifting away from that main goal. As systems improve, those narrow tactics tend to stop working and force constant catch‑up. This is why Google’s recent guidance concluded that there is “nothing really that different” you need to do just because AI formats are emerging, beyond continuing to create content that genuinely serves people.
You Don’t Need a Separate Strategy for Every AI Format
Many creators feel pressure to “do something new” for every new AI‑related term or search feature they hear about. In the past, people even made multiple versions of the same page for different search engines like AltaVista, WebCrawler, or Open Text, trying to tune content to each one’s quirks. Over time that proved unnecessary because search engines largely aimed at similar goals and the differences between them narrowed.
The same pattern applies today with AI search features. Trying to maintain separate content strategies for every AI label or mode risks making things more complicated without reliable long‑term benefit. Instead, web creators are encouraged to see AI formats as part of SEO, to understand how new formats apply to their world, and then decide whether there are a few specific adjustments worth making rather than reinventing everything.
From Technical SEO to Content‑First SEO
In earlier days of search, site owners often needed to handle many technical tasks just to be properly accessible in search results. Today, when using a popular CMS such as WordPress or Wix, much of that technical foundation is handled for you by default. This shift means the technical layer is less prominent for typical creators, allowing them to focus more on the content itself.
That transition reflects what users actually care about: the quality and usefulness of what they read, watch, or listen to. Technical SEO still exists, but for many web creators, the biggest gains now come from improving their content rather than obsessing over minor technical tweaks. This perspective aligns with Google’s emphasis on great, satisfying experiences, regardless of whether results appear as traditional listings or AI‑driven snippets.
Why Chasing Short‑Term SEO Tricks Doesn’t Last
The discussion touches on the familiar temptation to chase specific tactics that seem to produce outsized results. Sometimes site owners discover a particular trick that brings more success than expected and feel compelled to lean into it. However, these isolated wins tend not to last because they are focused on one narrow angle instead of the overall goal of serving users well.
As ranking systems evolve and more factors come into play, that one “magic trick” stops working. An example is websites that built large amounts of traffic on commodity answers, such as daily solutions for popular word games. That model works only until systems can reliably provide those answers directly, at which point the traffic quickly erodes. When a site’s strategy is built on this commodity layer, it is highly vulnerable to changes that remove the need for those thin answers.
Original Content Beats Commodity Information
One of the strongest themes in the conversation is the importance of original content rather than commodity information. Commodity content covers simple factual queries that AI systems already handle well, such as “What time is the Super Bowl.” For years, many sites created long posts around this kind of question, wrapping a simple answer in unnecessary text just to capture traffic.
Over time, Google has been able to answer many of these questions directly using data feeds and structured information, which most users appreciate. For sites that depended on this type of traffic spike, that change is a setback, but it also reveals a strategic weakness: their content wasn’t built on a unique voice or perspective. The real strength of a publication lies in original takes and insights that only that creator can provide.
Authenticity and Firsthand Experience Matter More
People increasingly want original content that feels authentic and grounded in firsthand experience. That might appear as videos, podcasts, social posts, or written articles where creators share their perspective and expertise. Search already reflects this by bringing more social and experiential content into results alongside traditional expert articles.
Users often want both expert analysis and real‑world experiences side by side. If you already produce expert takes in written form, there is an opportunity to repurpose that strength into other formats such as video or audio. The key is that the core remains your genuine knowledge and voice, not manufactured authenticity or content created purely to match a pattern.
Why Multimodal Content Helps in AI and Traditional Search
The term “multimodal” may sound abstract, but here it simply means that people can search in one way and receive information in another. A practical example is taking a short video of geese, sending it through a search app, and receiving a text explanation that they are eating grass. Other everyday uses include snapping a picture of an item to ask what it is worth or how to fix it without even typing the name.
For site owners, this shift means that having a mix of text, images, and video can create more opportunities to appear in these richer search experiences. If your content has mostly been text‑based, adding original visuals and videos can help align with how modern search connects queries, media, and answers. This approach benefits both AI features and traditional search because some questions are simply easier to answer with a video embedded in a blog post than with a long block of text alone.
Structured Data As a Helpful Signal, Not a Silver Bullet
Structured data is mentioned as another area that creators should consider, but not as a magic solution. Adding the right structured data can already help with existing search features, and it has potential value for newer AI‑driven formats as well. The guidance is to think about it as something useful to include where appropriate, rather than a secret shortcut to success.
Without structured data, a site is not automatically excluded from AI experiences or other search features. Instead, structured data is presented as one more way to help systems understand your content more clearly. It fits into the broader pattern: focus on core value first, then layer on technical enhancements that reinforce that value instead of relying on them as the main strategy.
Redefining Success Beyond Raw Clicks
When it comes to measuring success in this new search environment, Danny emphasizes the need to go beyond counting clicks. Many site owners still default to “I got a lot of clicks” as their primary metric, without clearly defining what real success looks like for their business or project. Instead, they are encouraged to measure quality clicks and meaningful conversions, tailored to their own goals.
For some, that conversion might mean collecting email addresses to build an ongoing relationship; for others, it could be purchases, sign‑ups, or deeper engagement with content. Early data suggests that traffic from newer AI formats often arrives in a more engaged state, with visitors spending more time on site. That increased engagement can be a proxy for better alignment between what people expect and what they find when they click through.
How AI Answers Improve Searcher Context
AI‑driven formats such as AI Overviews can accelerate the way people refine their searches and understand a topic. Traditionally, someone might start with a vague query, click several results, and iteratively adjust their search until they finally reach the page that truly matches their need. AI formats can simulate that process by running many related searches behind the scenes and then composing an answer based on the broader set of results.
This mechanism, described as “query fan out,” means that the AI answer is informed by multiple queries rather than just the one typed into the box. As a result, when someone clicks from an AI answer to a website, they may already have a clearer idea of what they are looking for. That higher level of contextual awareness helps explain why visits from these formats can be more engaged and potentially more valuable for site owners.
Why Keyword Tools and Exact Phrases Matter Less
Historically, SEOs relied heavily on keyword tools to decide which specific word or phrase to target, such as choosing between two competing labels for the same concept. Over time, search engines became better at understanding variations in language, so exact matches became less critical. Nevertheless, many practitioners still feel the pull of older habits and run back to tools for every nuance.
With people now typing full questions or long conversational queries, trying to optimize pages for every possible sentence would be impossible and counterproductive. The guidance is not to create a separate page for each long query but to focus on the underlying topic and cover it in a way that makes sense to a human reader. The emphasis is again on writing for people first, trusting modern systems to map those natural texts to the many ways users might ask for the same thing.
Focus on Original, Authentic, Multimodal Content and Real Outcomes
Across the entire discussion, several core priorities stand out for SEO in an AI‑driven world: focus on original content, stay authentic, embrace multimodal formats where they make sense, and measure success based on real outcomes rather than raw click volume. The fundamentals of SEO still apply, even as formats and interfaces become more sophisticated.
Creators who lean into their unique voice, share genuine experience, and give users what they truly need are better positioned to thrive as search evolves. Rather than chasing each new acronym or quick win, they can anchor their strategy in serving people first and let technical enhancements, structured data, and AI formats support that foundation.