Timeless SEO rules AI can’t override: 11 unshakeable fundamentals

Today’s AI-driven search might look radically different on the surface, but the core principles of SEO remain as critical as ever. 

Yes, AI overviews, zero-click SERPs, and entity-based results have changed how users get information. And if you’re brave enough to take a look at Search Console, your impressions are soaring even as clicks decline.

But the sites winning today are still doubling down on SEO fundamentals while embracing experimentation to support how AI agents interpret content. 

In this case, the north stars haven’t shifted. And a focus on clarity, credibility, and connection still leads the way. 

11 SEO fundamentals that still matter

That’s why in this write-up, we’ll break down 11 rules that still drive results, no matter how search keeps reinventing itself. Each rule is defined and explored in the context of AI-overhauled search, with current examples, expert insights, and practical tips you can apply right now.

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Heads up: If Google’s new AI answers are scraping your content without always sending traffic, don’t panic. These rules will help you capture value despite the “great decoupling” of impressions and clicks. And navigate measurement blind spots, entity optimization gaps, publisher value challenges, and strategic uncertainty.

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1. Put user intent first and optimize for people

No matter how fancy (or cluttered) a search interface gets, SEO still begins and ends with serving the searcher. 

You need to truly understand your audience and what they need your content to deliver. That’s how you stand out in AI-infused results. 

As Marcus Miller puts it: “Know your audience. Create personas, gather feedback, and define their goals, pain points, and the jobs they rely on your product or service to support.”

Because generative results don’t reward clever keyword tricks. They reward the best answer. 

Kevin Indig’s analysis of AI search behavior argues that the game has shifted: It’s less about matching a single query and more about comprehensively covering the topic and its related intents (the “query fan-out” effect).

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Miller’s guidance doubles down on that reality: “Create content worth quoting… Anticipate the full conversation… If someone asks, ‘How does AI change SEO?’ they’ll also want to know, ‘What should I do about it?’ Build that into your content.”

Zooming out, that means still writing your content for people first. 

So, less focus on keywords and more focus on realistic queries (which, let’s be honest that should have been your approach for a while now anyway).

What this means in practice

• Shift from keywords → topics & questions. Map the main task a searcher is trying to complete, then list the natural follow-ups they’ll ask next. Miller’s “anticipate the full conversation” rubric is a clean litmus test for your outlines.
• Write for answers, not just rankings. Lead with a clear, direct answer, then support it with context, steps, and examples. This structure plays well for humans and makes your page easier to cite in AI summaries.
• Use tools to capture real intent. Build question lists from Semrush (Keyword Magic) or SERP features (People Also Ask) and validate with customer inputs (surveys, interviews, call notes). Then group those lingering questions into sections/FAQs so you cover the “whole conversation,” not just the head term.
• Favor semantic coverage. Where you once targeted one query per page, design content to cover the entity/topic and the cluster around it. Indig’s “query fan-out” research shows AI expands a user’s prompt into many related sub-queries. So, you can win by answering the set, not just the seed.

AI systems summarize from sources that demonstrate complete and trustworthy coverage. When your page anticipates the next questions and connects the dots (vs. chasing a single phrase), you increase your odds of being retrieved, quoted, or linked from those answers. 

2. Build with credibility

Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) remain at the core of every search update.

AI hasn’t changed that. If anything, it’s made quality signals more important.

Google’s own guidance states that it rewards “original, high-quality, people-first content that demonstrates E-E-A-T,” regardless of whether a human or AI helped create it. Generative systems like Google’s Search Generative Experience (SGE) and Bing Chat still depend on trusted, authoritative sources. 

They can’t risk surfacing outdated, thin, or inaccurate information. So the content they summarize tends to be the same content that already ranks well organically.

As SEO expert Lily Ray explains, AI Overviews rely on real-time retrieval from Google’s index and the same ranking signals used in traditional search. That means the formula hasn’t changed: Original research, accurate information, and useful answers still win.

Marcus Miller frames AI’s desire for credible sources as a new (or maybe just revived?) opportunity for those who can provide “something new and worth citing.” 

He also warns of “model collapse.” AI systems becoming less accurate as they train on regurgitated AI content. Leaving an opportunity for fresh human insight and firsthand experience.

That’s where E-E-A-T comes in. Content that shows real expertise and trust signals—bylines with credentials, clear sources, recent updates—is far more likely to be featured in AI summaries. 

As the Quality Rater Guidelines note, low-effort or unoriginal content (including AI fluff with no added value) is considered low quality. The antidote is originality and experience that readers can verify.

What this means in practice

• Audit for depth & originality. Remove or rewrite thin pages. Add real-world examples, data, or case studies where you can.
• Show the humans behind the content. Include author bios with credentials and an “About” page that explains your expertise.
• Back up every claim. Cite reliable primary sources and link to data from recognized industry authorities. It builds reader trust and gives AI more reason to see you as credible.
• Add fresh insights. Conduct mini surveys or polls. Publish small studies or firsthand observations from your own experience. AI systems crave new data points they can reference.
• Keep content current. Update facts, screenshots, and links regularly; freshness is a trust signal in both human and AI ranking.

AI models pull from the most credible content they can find. Pages that clearly demonstrate experience, expertise, and authentic value tend to surface more often. Make yourself the trusted source that AI relies on and amplifies.

3. Maintain a rock-solid technical foundation

Even in a world of AI-powered answers, the oldest rule in SEO still stands: If search engines can’t crawl or index your site, your content doesn’t exist. 

Why? Because most use retrieval-augmented generation. They fetch up-to-date web content from Google and Bing results to build responses.

This is why the fundamentals that make your pages technically sound still matter. Valid HTML, proper status codes, HTTPS security, and clean architecture are the bare minimum to be seen. 

AI hasn’t changed the value of a structured organization either. Clean URLs, descriptive file paths, and up-to-date XML sitemaps make it easier for crawlers to understand your site. 

If a page is buried too deep or marked “noindex,” it’s invisible to both search and AI. Structured data (covered later) and organized sitemaps help search engines—and by extension, AI models—understand your content faster and more accurately.

And page experience factors? Like speed and mobile performance, they also play a role, with Google essentially confirming that Core Web Vitals act as a tiebreaker ranking signal. Sure, they may not determine your position outright, but they can separate two otherwise equal pages.

What this means in practice

• Run regular audits. Use Semrush Site Audit or Google Search Console to spot crawl errors, missing canonicals, or blocked pages.
• Track index coverage. Monitor how many pages are indexed vs. submitted. If important pages aren’t showing, check for crawl depth, duplication, or disallowed parameters.
• Keep your sitemap clean. Submit an XML sitemap listing every key URL; it provides the clearest map of your site to search engines and AI crawlers alike.
• Optimize speed. Compress images, use a CDN, and remove unused scripts. Fast pages make both users and bots happy.
• Review after major changes. Re-check indexing and crawl stats after migrations, design updates, or CMS changes to catch issues early.

Technical SEO is invisible when done right—but everything else depends on it. Crawlability, site structure, and index health form the foundation that every AI summary and ranking signal stands on.

4. Design for a quality user experience

Why does UX still matter when AI answers might give users what they need before ever visiting your site? 

Two big reasons:

1. When a user clicks through from an AI Overview or SERP feature, you need to win them fast. A slow, clunky site drives instant bounces.

2. Search engines still rely on user experience signals—directly and indirectly—when deciding which pages to rank or feature.

As we already mentioned, Core Web Vitals and mobile usability remain part of Google’s algorithmic considerations. While these signals are relatively lightweight, they still influence visibility when two pages are otherwise equal. Bing’s AI-driven results follow a similar logic, favoring pages that are readable, secure, and well-structured.

And here’s the encouraging part: early data suggests that AI-driven visitors often engage more deeply than traditional organic traffic. These users are typically in “research mode,” clicking through to verify details or explore related insights. 

When they arrive, your UX determines whether that curiosity becomes trust. Or just a missed opportunity.

What this means in practice

• Design for mobile first. Use responsive layouts and test across devices. Run Google’s Mobile-Friendly Test to catch common issues like tiny text or touch elements that sit too close together.
• Boost site speed. Compress images, enable caching, and remove or defer non-essential scripts. Use PageSpeed Insights to find slow pages.
• Monitor Core Web Vitals. Check metrics like Largest Contentful Paint and Cumulative Layout Shift in Google Search Console. Aim to stay in the “good” range across as many pages as possible.
• Simplify navigation. Keep menus logical and consistent. Avoid intrusive interstitials or autoplay content that frustrates users and breaks engagement.
• Watch engagement metrics. Look for high-bounce or low-time-on-page URLs—especially those showing impressions in AI results—and prioritize improving them.

AI may limit clicks, but the ones you do earn matter more than ever. When every visit counts, speed, clarity, and usability are what turn an AI-driven impression into a meaningful interaction.

5. On-page best practices make you findable

On-page SEO might feel basic, but it’s the framework that helps both humans and algorithms understand what your content is about.

AI Overviews often display your page title or use it to infer context. A well-written, descriptive title can attract clicks, even within an AI-generated summary. And even when a click doesn’t happen, it still reinforces brand awareness. 

Meta descriptions may not always appear in AI-generated answers (and are actively being rewritten), but they still inform how your content is presented elsewhere. They may also act as an emerging summary signal.

On-page optimization also extends beyond keywords. Search today is more semantic, but AI still depends on clear topical signals. 

Cover your core topic thoroughly, incorporating related terms and subtopics naturally. As Danny Goodwin explains, “it’s not about exact queries, it’s about semantic relevance.” Solid on-page structure ensures search engines—and AI systems—can confidently match your content to the right questions.

Formatting also matters for machine readability. 

Lists, tables, and FAQs make your information easier for AI to parse and summarize. If you publish step-by-step guides, use ordered lists (“How to do X in 5 Steps”) to increase the chance that your process appears directly in an AI result. 

Structured formatting benefits accessibility, featured snippets, and AI all at once.

What this means in practice

• Refine your meta titles and headings. Create concise, keyword-rich meta titles (under ~60 characters) and ensure each page has a matching H1 that clearly conveys its topic.
• Structure with intent. Use H2s and H3s to organize logical sections. Include secondary keywords or questions where it feels natural.
• Write for topics, not strings. Weave in related entities and concepts. For example, a page on “content marketing strategy” should reference planning, audience research, promotion, and measurement.
• Optimize for clarity. Write meta descriptions that entice readers to click by explaining the benefit or takeaway.
• Leverage schema markup. Add FAQ or HowTo schema where relevant; these often power featured snippets and AI summaries.

Algorithms—no matter how advanced—still need context. A well-optimized page gives them the signals they need to understand, rank, and surface your content. 

The clearer you make those signals, the more likely your pages will appear wherever search (and AI) decide to look.

6. Leverage structured data and entities

Schema markup and other structured data formats give machines explicit context. 

That context influences everything from rich results and carousels to knowledge panels and AI-generated summaries. 

As Aleyda Solis explains, adding schema markup helps AI systems like Bing’s ChatGPT-powered search better interpret page information—and Microsoft has confirmed that structured data aids its understanding of web content. Google’s Search Generative Experience (SGE) also taps into structured data to identify credible sources and produce more accurate answers.

Why does this matter? Because search is shifting toward entities and their attributes. Referencing people, organizations, products, and concepts. 

AI models build knowledge graphs to answer queries based on these relationships. If your brand or authors aren’t clearly linked to recognized entities, your visibility suffers. 

Implementing schema (Organization, Person, Product, FAQ, HowTo, etc.) gives search engines a direct map of who you are and what you offer.

Without structured signals, AI systems may fill in the blanks with incomplete or inaccurate information. But by defining your own data—through schema, Wikipedia, Google Business Profile, or Wikidata—you ensure accuracy and maintain control over how your brand is represented.

What this means in practice

• Add high-impact schema. Use Schema.org markup for key types:
  • Article (with author info and publication date)
  • FAQ or HowTo for step-based or instructional content
  • Product and Review for ecommerce pages
  • Organization and Person for brand and author details
• Use JSON-LD format. It’s Google’s preferred method. Validate your markup with the Rich Results Test and fix any issues flagged in Search Console.
• Strengthen your entity presence. Create or update a Wikipedia page (if applicable) and link to it with sameAs schema. Connect your brand to verified social profiles and external data sources.
• Link your entities internally. Add author bio pages (with markup) and connect them to every article. This builds an internal web of contextual signals across your site.
• Monitor rich results. Use Google Search Console’s Rich Results report to track coverage, errors, and enhancements.

Structured data is the language search engines—and AI systems—speak fluently. The clearer your site communicates in that language, the more accurately and confidently it will be represented in SERPs, AI summaries, and beyond.

7. Build authority with backlinks and mentions

Every few years, someone declares that “links are dead.” 

Yet, backlinks remain one of the strongest credibility signals for search engines and AI systems. 

Search engines still need ways to gauge authority. And links from credible domains remain their best indicator. Even unlinked brand mentions help establish entity authority. Something large language models use when deciding which sources to reference or cite.

Think of it this way: When Google’s AI Overview builds an answer, it favors sources that have earned industry trust. 

A page with strong backlinks signals to both Google and Bing that it’s reliable, relevant, and widely recognized. 

Having a robust backlink strategy also cushions against reduced organic clicks. If AI overviews or zero-click results cut into traffic, referrals from news outlets, niche publications, and partner sites become even more valuable. 

Getting featured in a reputable publication—say Wired or The BBC—earns both visibility and validation. It’s digital PR in its truest form: building backlinks, brand citations, and E-E-A-T all at once.

What this means in practice

• Create link-worthy assets. Develop content that others want to reference—original research, data visualizations, or expert insights. These naturally attract links over time.
• Use digital PR for outreach. Pitch stories, statistics, or commentary to journalists in your niche. One link from a major publication can outweigh dozens of lower-quality ones.
• Leverage media tools. Use Help A Reporter Out (HARO) or similar platforms to contribute quotes and earn backlinks.
• Track brand mentions. Tools like Semrush Brand Monitoring can find unlinked citations; reach out and request proper attribution.
• Build relationships. Guest post on respected industry sites or collaborate on co-branded resources. Consistent exposure reinforces authority signals.
• Pass authority internally. Link from your most authoritative pages to newer or less visible ones. Internal linking distributes link equity and strengthens your topical clusters.

Links remain the web’s native reputation system. 

They show both users and algorithms which sources deserve trust. As Google continues refining how it evaluates authority, backlinks—and the brand credibility they represent—will stay central to how both search and AI determine what’s worth amplifying.

8. Go deep and think beyond the current page

AI systems and search algorithms both look for signs of topical depth. The “best” page on a subject is often the one supported by a network of related content. 

From a crawl perspective, well-linked pages get revisited more often. Orphaned pages risk being ignored by both crawlers and AI retrieval systems.

For example, if you have a comprehensive guide to “email marketing” that links to subpages on “email design,” “list building,” and “analytics,” Google recognizes that you cover the topic thoroughly. This hub structure can elevate your pillar content’s visibility and increase the odds it’s chosen as a trusted AI source.

What this means in practice

• Map your content architecture. Organize your site into logical categories or topic clusters. Each major topic should have a hub page linking to its subtopics—and those subtopics should link back up.
• Use descriptive anchor text. Avoid vague phrases like “click here.” Instead, use natural anchors that signal context—like “SEO periodic table” or “email marketing analytics.”
• Keep important pages accessible. Make sure every key URL is within a few clicks of the homepage or another high-traffic page. Deep or isolated pages lose crawl priority.
• Leverage high-authority pages. Identify the pages with the most inbound links or traffic (via Semrush or Google Analytics) and use them to pass link equity to newer or lower-visibility pages.
• Use navigation elements wisely. Add links to cornerstone content in sidebars or footers when appropriate. “Related articles” widgets can help—just ensure they’re actually relevant.
• Maintain clear hierarchy. Use logical, clean URLs (e.g., site.com/topic/subtopic) and breadcrumbs to clarify structure for both users and search engines.

A site with clear topical connections gives algorithms a stronger signal of authority and provides AI with a better map of where to find your most useful content.

9. Diversify your content beyond Google

Don’t build your entire strategy around one platform. Search is bigger than Google now, and the brands that win long term show up wherever their audience is looking.

Some experts call this “Search Everywhere Optimization.” But don’t get too caught up in adopting another search-related acronym. Search performance has long been influenced by a brand’s presence on other platforms.

LLMs have just heavily tilted their level of influence.

That means YouTube, TikTok, Reddit, Instagram, podcasts, and even chat interfaces all function as discovery tools. 

This matters because every one of those channels now feeds into your brand’s authority. 

When fewer clicks come from Google, the next best clicks are the ones you generate yourself—through social, video, and direct engagement. That’s how you offset publisher value erosion and build resilience.

If someone discovers your tutorial on YouTube, reads your article on LinkedIn, and then finds your name again in Google’s AI Overview, that repetition builds familiarity and trust. 

As Lily Ray points out, AI answer engines are drawing from both authoritative sources like Wikipedia and community-driven platforms like Reddit. Places where brands can’t easily control the conversation.

That shift makes it even more important to strengthen brand mentions and diversify where your expertise shows up. The more your content, insights, or commentary appear across trusted sources, the better positioned your brand is to be referenced.

What this means in practice

• Go where people search. Launch or optimize a YouTube channel. Post tutorials, explainer clips, or interviews, and always include transcripts for indexing.
• Lean into social search. Create short-form videos or carousel posts for platforms like TikTok, Instagram, or Pinterest that answer real questions (“how to,” “tips,” “ideas,” “mistakes to avoid”). Start by looking at searches where shorts and videos appear in search results to increase your chances of content making a more direct impact.
• Expand your footprint. Contribute articles to LinkedIn, Medium, or industry blogs. Answer questions on Quora or Stack Overflow. These off-site mentions often rank in SERPs and feed into AI knowledge sources.
• Watch where growth happens. Track referral traffic, engagement on embedded media, and mentions across platforms. If Reddit or YouTube impressions are climbing, double down.

Diversifying your reach protects your visibility from dependency. The more places your expertise appears, the more resilient your business becomes when search behavior shifts or algorithms change.

And in turn, the more likely your content will be recognized and surfaced by AI models in the process.

10. Evolve your SEO measurement to prioritize visibility

What gets measured gets managed. And in SEO, what we measure should be changing. 

Clicks and rankings used to tell the story. Today, with AI answers, zero-click results, and shifting user behavior, those metrics paint a dismal and incomplete picture.

That’s not to say clicks don’t matter. As Cyrus Shepard mentioned, clicks are a clear sign of support for information. But at the same time, traffic is declining and not going back to previous levels.

That doesn’t mean SEO value is disappearing. It just means we can’t place success solely on impressions and CTR. Success now includes visibility, engagement, and downstream influence, even when clicks are fewer.

Start by monitoring impressions and share of voice more closely. Understand how much of the overall pie for queries and topics you care about you currently own. And start to include brand mentions in LLMs as part of this reporting.

Also track indirect conversions. 

Users might discover your brand in a zero-click result and convert later without ever clicking a search listing. Monitor branded search volume and direct traffic fluctuations to see if awareness grows after key content appears in search. 

Lastly, give more credence to engagement metrics. They carry more weight now, too. Time on page, scroll depth, and return visits show how valuable your traffic really is. 

Those are numbers worth showing your stakeholders.

What this means in practice

• Broaden your dashboards. Report beyond clicks and rankings. Include impressions, share of voice, and SERP feature visibility. If Bing or other tools start reporting “AI citations,” track those too.
• Calculate your search footprint. Combine impressions, top-result appearances, and competitor comparisons to tell a more complete visibility story.
• Correlate with conversions. Partner with your analytics or BI team to connect impressions or visibility lifts to downstream conversions—even if the attribution looks “direct.”
• Measure engagement quality. Track dwell time and repeat sessions. Rising engagement can indicate you’re attracting the right users, even if traffic totals flatten.
• Capture qualitative feedback. Encourage sales or service teams to note when prospects mention finding you through AI summaries or snippets.

As Michael King put it during his SMX Advanced presentation, “SEO isn’t dead; it’s deprecated.” 

That’s why modern SEO measurement must focus on total visibility, influence, and quality of engagement. When you track those, you see how your efforts continue to drive growth. Even when the clicks themselves don’t.

11. Adapt but hold true to fundamentals

The last rule is more of a mindset shift. Adapt quickly, but don’t abandon what’s always worked.

AI has introduced new questions for every SEO team: 

Will rankings still matter? How do we optimize for answer engines? What happens when clicks keep declining? 

But SEO has lived through plenty of “end of SEO” moments before—mobile-first indexing, voice search, core updates—and it always comes out stronger.

The reality is Google’s ranking systems—AI included—have and will keep refining how they assess credibility. Investing in a consistent, trustworthy presence today is the best way to stay ahead and compete against more established brands.

As Olaf Kopp explains, “Companies should prioritize the co-occurrence of their brands and products with relevant attributes and entities while optimizing for these relationships in qualified media.” 

In simpler terms, focus your content on topics where your brand has real expertise, perspective, and relevance. So search engines (and AI models) learn to associate your name with authority in that space. 

That’s what authority looks like in an AI-driven landscape—visibility built through verified connections, not quick wins. 

It’s a longstanding strategy that sits above any single algorithm or platform. And it will last far beyond hacky SEO tactics like scraping a competitor’s sitemap or flooding the web with flimsy AI-generated content. 

Deep investments in understanding your users, publishing quality content, and earning trust aren’t going anywhere.

What this means in practice

• Experiment often. Test new formats, track how tools like Bing Chat or Google’s SGE interpret your pages, and share insights with your team.
• Audit quarterly. Don’t let AI tools distract you from the basics: site health, crawlability, link profile, and content freshness.
• Stay consistent. Revisit your top-performing content. Update statistics, add examples, and expand sections that drive engagement.
• Focus where you add value. Prioritize topics and formats where you can demonstrate genuine expertise—generic content will get buried fast.

Most importantly, keep perspective. SEO has always been a long game. 

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SEO isn’t dead

AI isn’t ending SEO. It’s maturing the discipline. 

The fundamentals still win: understand your audience, meet their needs, and communicate clearly wherever they find you. That’s one thing AI can’t replace or replicate. 

Amid the chaos and constant change, the most successful teams aren’t the ones chasing every update. 

They’re the ones who adapt, stay consistent, and keep moving forward. SEO has always been about resilience. This chapter is no different.

For a deeper look at how to evolve without starting from scratch, read 6 Easy Ways to Adapt Your SEO Strategy for Stronger AI Visibility. It will help you put much of what we covered today into practice.