You’ve worked hard to build your product catalog. The last thing you want is AI tools like ChatGPT or Google Gemini describing your products inaccurately to potential customers.
AI tools don’t browse your whole store the way a search engine does. They grab what they can find, quickly, and fill in the gaps. For a store with a large catalog, that means incomplete answers, outdated information, or worse, sending shoppers to a competitor.
The new llms.txt feature, available in Yoast SEO for Shopify bridges that gap.
What does it actually do?
It creates a file that tells AI tools which parts of your store matter most: your top products, your collections, your policies, and your key pages. Think of it as handing AI a well-organized store guide instead of letting it wander around on its own.
You switch it on once. We handle the rest.
Two ways to use it
Let Yoast handle it automatically
Turn it on and we’ll build and update the file each week based on your Shopify data. No decisions needed. The file automatically highlights:
Your 10 most-sold products over time
Up to 5 of your largest collections, plus a link to your full product range
Your store policies, including shipping, returns, and privacy
Your homepage, latest blog posts, and most recently updated pages
Any pages you’ve already marked as cornerstone content
Or choose exactly what’s included
If you’d rather have full control, switch to manual selection. You can hand-pick the products and pages you want to feature, and there’s a dedicated spot to add your “About us” page so AI knows the story behind your brand.
Either way, the file updates weekly and removes deleted products automatically.
No technical knowledge needed
Setting this up from scratch would normally mean editing code. We’ve built it directly into your Yoast SEO for Shopify settings so any member of your team can turn it on in seconds. If you already have a redirect set up for /llms.txt, we’ll respect it and let you know, so nothing breaks.
You decide when it’s right for your business
We believe every merchant should have a say in how their content is seen and used as AI plays a bigger role in how people discover products online. That’s why this feature is opt-in.
Turn on the llms.txt toggle in Yoast SEO for Shopify next time you log in to your store.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2026-03-31 08:04:572026-03-31 08:04:57Introducing llms.txt to Shopify: Give AI a map to your best products
AI search is changing how visibility works. Users are getting direct answers instead of clicking links, which means fewer chances to drive traffic. In this shift, AI citations are becoming the new gatekeepers, deciding which sources get featured in answers. Over the past year, search has moved from ranking pages to selecting sources, pushing us from traditional SEO toward AI-driven visibility.
In this article, we’ll explain what AI citations are, how they work, and how you can earn them.
AI citations are references that search engines include in AI-generated answers, enhancing credibility and visibility
This shift in visibility moves from traditional SEO ranking to AI-driven inclusion as a key factor for brand presence
AI tools retrieve information from diverse sources, with citations coming from both top-ranking and deeper pages
To earn AI citations, create valuable, structured content and establish topical authority across your niche
Tools like Yoast AI Brand Insights help track your AI visibility and citation presence across platforms
What are AI citations?
Citations have always been a way to show where information comes from and why it can be trusted. The same idea now applies to AI-generated answers.
ChatGPT cites resources in its answer
AI citations are the references that search engines and AI tools include to support the answers they generate. When a tool like ChatGPT responds to a query, it often points to specific pages or sources that back up the information. These references act as signals of credibility, helping users understand where the answer is coming from and giving them a way to explore the original content.
In simple terms, if your content is cited, it becomes part of the answer itself, and not just another link in the results.
AI citations vs the blue link era
If AI citations determine what gets included in answers, it’s worth asking how this differs from how search used to work. Because this isn’t just a feature update, it’s a shift in how visibility itself is earned.
In the traditional model, ranking higher meant getting more clicks. In AI-driven search, being selected as a source matters just as much, if not more.
Aspect
Traditional SEO
AI citations
Visibility
Blue links
Ai-generated answers
Traffic
Click-driven
Influence-driven
Authority signal
Backlinks
Credibility and accuracy
User action
Visit website
Consume instant answers
This doesn’t mean traditional SEO is going away. Rankings, indexing, and backlinks still play a critical role. However, how that value gets surfaced is changing. Instead of just competing for position on a results page, you’re now competing to be part of the answer itself.
Do check out Alex Moss’s talk at BrightonSEO, 2025, on the evolution of search intent and discoverability.
Where do AI citations come from?
Before you try to earn AI citations, it’s important to understand where they actually come from. Because you’re not just competing with other blog posts, you’re competing with an entire information ecosystem.
AI models pull their answers from a mix of sources:
Web content: Blog posts, guides, landing pages, and long-form articles
Structured sources: Platforms like Wikipedia, documentation hubs, and product data feeds
Forums and UGC: Discussions from Reddit, Quora, and Stack Overflow
First-party data: Brand websites, help centers, and official resources
How the sources are selected is quite interesting. A recent analysis of Google’s AI Overviews found that citations don’t strictly come from top-ranking pages. In fact, only about 38% of cited sources rank in the top 10 results, meaning a large share comes from deeper pages or alternative formats.
Another key insight by CXL: AI models tend to prioritize clear, early answers within the content, with a significant portion of citations pulled from the top sections of a page rather than from deeper sections.
The takeaway is simple. AI systems are not just ranking content; they are selecting the most useful pieces of information across formats and sources. That means your content is competing not only for rankings but also for clarity, structure, and trustworthiness across this entire ecosystem.
Types of AI citations
Not all AI citations look the same. Depending on the query and intent, AI models pull in different types of sources to support their answers.
Broadly, you’ll see three main types:
Informational citations
These are the most common. AI tools refer to blog posts, guides, and educational content to explain concepts or answer questions. If someone asks, “what are AI citations,” the sources cited will typically be long-form, explanatory content.
Informational citations made by ChatGPT
Product citations
These show up in commercial or comparison queries. For example, “best SEO tools” or “top project management software.” Here, AI models cite product pages, listicles, and review-based content to support recommendations.
Product citations by Google AI mode, the model shares both online and offline options
Multimedia citations
AI doesn’t rely solely on text. Videos, images, and other visual formats can also be cited, especially when they better explain something than text alone. Think tutorials, walkthroughs, or demonstrations.
Multimedia citation for a query by ChatGPT
How AI citations impact brand credibility
AI citations don’t just drive visibility. They shape how your brand is perceived before a user even visits your website.
When your content is cited in an AI-generated answer, some of that trust transfers to your brand. You’re no longer just another result on a page; you’re part of the answer itself. And that changes how users interpret your authority.
This also means buyer decisions are starting earlier. Users may form opinions, shortlist options, or even make decisions directly from AI responses, without ever clicking through. If your brand isn’t cited, you’re not part of that consideration set.
There’s also a strong signal of relevance at play. Being included in AI answers suggests that your content is not just optimized, but genuinely useful in context. It tells both users and algorithms that your brand deserves to be surfaced.
Over time, this creates a compounding effect. The more your content is cited, the more your brand becomes associated with specific topics. That repeated exposure builds familiarity, authority, and trust.
How AI citations work: a complete breakdown
So far, we’ve talked about what AI citations are and where they come from. But how do AI systems actually decide what to cite?
Let’s break it down.
A diagram by AWS showing the conceptual flow of using RAG with LLMs
At a high level, most AI-powered search systems follow a retrieval-and-synthesis process, often powered by approaches such as Retrieval-Augmented Generation (RAG). In simple terms, they don’t just generate answers; they find, evaluate, and assemble information from multiple sources before deciding what to cite.
Here’s what that process looks like in practice:
1. Query understanding
Everything starts with intent. The AI interprets what the user is really asking, whether it’s informational, navigational, or commercial. This step shapes what kind of sources it will look for.
2. Retrieval of sources
Next, the system pulls in potential sources from multiple places:
Web indexes
Training data patterns
Live retrieval systems (depending on the model)
This is where your content first enters the consideration set.
3. Source evaluation
Not all sources are treated equally. AI models evaluate them based on:
Relevance to the query
Authority and trust signals
Clarity and structure of information
Entity-level trust (how credible the brand or author is)
When you look at these signals closely, they all point in one direction. Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) play a central role in determining what gets cited. In other words, AI systems aren’t just looking for answers; they’re looking for reliable sources behind those answers.
4. Answer synthesis
Instead of showing individual links, AI combines insights from multiple sources into a single, cohesive answer. This is where your content may be used, even if it’s not directly cited.
5. Citation selection
Finally, the model decides which sources to:
Explicitly cite (with links or references)
Implicitly use (without direct attribution)
This is the step that ultimately determines your visibility.
How this differs across AI systems
While the core process is similar, different AI tools prioritize different parts of this pipeline.
AI systems
How it handles citations
ChatGPT
Leans more on third-party sources and consensus, such as directories, reviews, and aggregator sites, rather than relying heavily on brand-owned content.
Perplexity
Focuses on retrieval-first behavior, pulling from a wide range of web sources and surfacing multiple citations to support transparency (strong emphasis on external validation).
Gemini
Prioritizes brand-owned and structured content, especially pages that are clearly organized and easy to interpret.
Even though the process is complex, the signals that increase your chances of being cited are surprisingly consistent:
Well-organized structure: Clear headings, bullet points, and logical flow make it easier for AI to extract information
Evidence-based reasoning: Content that references data, sources, or supporting claims is more likely to be trusted
Timeliness and relevance: Fresh, updated content often gets prioritized, especially for evolving topics
Authoritative voice and depth: Content that demonstrates expertise and covers a topic comprehensively stands out
Topical consistency: Brands that consistently publish around a topic are more likely to be recognized as reliable sources
The key takeaway here is simple: AI citations are not random. They are the result of a structured evaluation process in which clarity, trust, and relevance determine who is included in the final answer.
So far, we’ve looked at what AI citations are and how models decide what to cite. The next question is the one that matters most: how do you actually get cited?
Because this isn’t just about creating content, it’s about sending the right signals that your content is worth citing. Here are some strategies that can help you do exactly that:
1. Create citation-friendly content
Citation-worthy content goes beyond surface-level answers. It offers original thinking, clear explanations, and real value, helping AI models support their responses with confidence. In other words, it’s not just optimized, it earns references by being genuinely useful.
The following content types consistently get cited by AI models:
Content type
What to write
Why AI loves them
Original research
Studies or data that answer new or unexplored questions
Gives AI concrete evidence to support claims
Case studies
Real-world examples showing how something works in practice
Helps AI justify recommendations with proof
Thought leadership
Opinion-led content with unique insights or perspectives
Adds depth and diversity to AI-generated answers
News content
Timely, accurate coverage of recent developments
Fills gaps where training data falls short
2. Build topical authority (clusters)
AI models don’t just evaluate individual pages; they evaluate how consistently you cover a topic.
If you publish multiple pieces on a specific subject, each addressing different aspects, you signal depth, expertise, and reliability. That’s what topical authority is all about.
And this is where E-E-A-T naturally comes into play. The more consistently you demonstrate experience and expertise in a niche, the more likely your content is to be trusted and cited.
What to do in practice:
Create clusters around a core topic (pillar page/cornerstone content + supporting content)
Cover both broad and specific questions in your niche
Go beyond basic answers, add expert insights, examples, or real-world context
Keep your messaging and terminology consistent across content
AI systems evaluate content, but they also evaluate who is behind it.
Strong entity signals help models understand your brand, your authors, and your credibility within a topic. The clearer these signals are, the easier it is for AI to trust and cite your content.
What to do in practice:
Build clear author profiles with expertise and credentials
Maintain consistent brand mentions across your site and the web
Use structured data (schema) to define authors, organizations, and content relationships
Ensure your “About” and author pages clearly establish credibility
4. Earn external validation signals across the web
AI models don’t rely on a single source of truth. They validate information by cross-referencing multiple sources across the web.
That means your credibility isn’t built only on your website. It’s shaped by how consistently your brand shows up across trusted platforms. The more aligned and authoritative those signals are, the easier it is for AI systems to trust and cite your content.
Think of this as building a web-wide validation layer that reinforces your brand through multiple independent sources.
This is also where traditional SEO practices like link building evolve. It’s no longer just about backlinks, but about earning consistent, high-quality mentions that strengthen your entity across the web.
What to do in practice:
Contribute insights to reputable publications in your niche
Earn consistent mentions across industry blogs, directories, and review platforms
Be active in communities like Reddit, Quora, or niche forums
Run digital PR campaigns that reinforce your brand narrative across sources
5. Keep content fresh and updated
AI models prefer content that reflects current information.
Outdated content is less likely to be trusted, especially for topics that evolve quickly. Regular updates signal that your content is still relevant and reliable.
What to do in practice:
Refresh key articles with updated data, examples, and insights
Add new sections instead of rewriting from scratch where possible
AI models don’t read content the way humans do. They extract answers.
Most AI-generated responses are built by identifying clear, concise answer blocks within content. And increasingly, users prefer this format. In fact, according to a poll by IWAI, 67% of users find AI tools more efficient than traditional search for getting answers. That shift makes one thing clear: if your content doesn’t directly answer questions, it’s less likely to be surfaced or cited.
This means it’s not enough to include answers. You need to structure your content so those answers are easy to find, interpret, and reuse.
What to do in practice:
Lead sections with direct, concise answers before expanding
Use headings that mirror real user queries and intent
Break down complex topics into scannable, extractable sections
Add summaries, definitions, or key takeaways at the start of sections
Anticipate follow-up questions and answer them within the same content
Tracking AI brand presence with Yoast
By now, we know what AI citations are, how they work, and how to earn them. But here’s the real question: how do you know if you’re already being cited? And if not, how do you understand where your competitors are showing up and where you’re missing out?
As AI-generated answers become a key discovery layer, most traditional analytics tools fall short. They can tell you about traffic, but not whether your brand is being mentioned, how it’s being perceived, or which sources AI systems trust when referencing you. That’s a critical blind spot, especially as AI answers increasingly shape user decisions before a click even occurs.
Yoast AI Brand Insights helps you track and understand your AI visibility, citations, and brand mentions across platforms like ChatGPT, Gemini, and Perplexity, so you can move from guesswork to informed action.
Here’s what it enables you to do:
Sentiment tracking
Understand how your brand is being perceived in AI-generated answers. The tool analyzes keywords associated with your brand and shows whether the overall sentiment is positive or negative, helping you spot tone issues and shifts over time.
Citation analysis (brand mentions)
See when and where your brand is being cited. More importantly, understand which sources AI platforms reference alongside your brand, so you can identify citation gaps and opportunities to improve your presence.
Competitor benchmarking
See how you stack up against other brands mentioned in your prompts
AI visibility is relative. This feature lets you compare your brand’s citations, mentions, and sentiment against competitors, helping you understand who is being surfaced more often and why.
Question monitoring
AI search is driven by queries. With question monitoring, you can track specific brand-related or industry questions and see whether your brand appears in the answers, giving you direct insight into where you’re visible and where you’re missing.
AI visibility index
See your score, which is a representation of different AI signals
Instead of looking at isolated metrics, Yoast combines signals like citations, mentions, sentiment, and rankings into a single visibility score. This gives you a clearer picture of how your brand performs across AI systems over time.
The bigger picture here is simple: Yoast AI Brand Insights helps you understand your position in this new ecosystem, so you can strengthen your presence, close gaps, and ensure your brand is part of the answers your audience is already consuming.
FAQs on AI citations
AI citations can feel complex at first, especially as search continues to evolve. Here are answers to some of the most common questions to help you navigate them better.
Are backlinks different from AI citations?
Yes, they serve different purposes. Backlinks help your pages rank in traditional search, while AI citations determine whether your content gets included in AI-generated answers. In short, backlinks drive visibility on SERPs, while citations drive visibility within answers.
No, AI systems don’t always include citations. When responses are generated purely from pre-trained knowledge rather than retrieved sources, citations may not appear.
To test this, I tried the following prompts on ChatGPT:
Out of these, citations appeared in about half of the responses.
A clear pattern emerged:
Queries involving products, recommendations, statistics, or recent events were more likely to trigger citations
Queries focused on definitions or general knowledge often did not include citations
This shows that citation behavior depends heavily on the query type, intent, and context. Not every answer requires a source, but the more specific or evidence-driven the query, the more likely citations are to appear.
How do I direct AI models to the most important content on my website?
You can’t directly control what AI models choose to cite, but you can make it easier for them to understand and prioritize your content.
One effective way to do this is by using llms.txt, a feature in Yoast SEO. It creates a structured, LLM-friendly markdown file that highlights your most important pages, helping LLMs better understand your site when generating answers.
A smarter analysis in Yoast SEO Premium
Yoast SEO Premium has a smart content analysis that helps you take your content to the next level!
Think of it as a way to clearly communicate which content matters most, so when AI systems look for reliable sources, your key pages are easier to interpret and surface.
AI citations: The currency of the AI-driven web
AI citations are changing how users discover and trust information. They don’t just complement rankings; they reshape them by deciding which sources become part of the answer itself. In many cases, users no longer need to click to explore. If your content is cited, you’re visible. If not, you’re invisible.
This shift also changes what we optimize for. It’s no longer just about traffic; it’s about trust, relevance, and inclusion in the answer layer. As we explored in our recent read, Rethinking SEO in the age of AI, the central question for SEO is evolving. It’s no longer just, “Can Google find my website?” It’s now, “Does the AI have a reason to remember my brand?”
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2026-03-30 14:31:172026-03-30 14:31:17AI citations explained: how they work and how to get them
The March 2026 SEO Update by Yoast is part of our monthly webinar series covering the latest developments in search and AI. Hosted by Carolyn Shelby and Alex Moss, this month’s session explored how AI is reshaping search, Google’s latest moves, and what brands should prioritize now.
AI is moving beyond standalone apps, integrating into messaging platforms (like Claude’s Telegram/Discord support) and desktop environments (e.g., Meta’s My Computer). This shift makes AI more accessible but also blurs the lines between search and daily tools.
Why it matters: Brands must ensure their content is discoverable across multiple surfaces, not just traditional search engines.
Actionable takeaway:
Optimize for conversational queries and structured data to improve visibility in AI-driven tools.
Google’s patent for AI-generated landing pages
Google filed a patent describing a system that replaces traditional SERPs with AI-generated landing pages. This could signal the end of the “10 blue links” era, forcing brands to rethink how they measure visibility.
Why it matters: If Google shifts to AI-generated pages, traditional ranking metrics may become less relevant. Brands will need to control their narrative across multiple sources to ensure accuracy in AI responses.
Actionable takeaway:
Audit your content for clarity and structure (e.g., avoid excessive JavaScript, use clear headings).
Diversify your presence beyond your website (e.g., social media, YouTube, newsletters) to reinforce authority.
Markdown as a preferred format for AI
Markdown is gaining traction as a lightweight, AI-friendly format. WordPress.org now offers Markdown versions of pages, and tools like Cloudflare’s crawl endpoint make it easier for AI to parse content efficiently.
Why it matters: While Google downplays Markdown’s importance, other AI tools may rely on it for grounding responses. Simplifying your content structure could improve visibility in AI-driven search.
Actionable takeaway:
Consider offering Markdown versions of key pages (e.g., FAQs, product descriptions) to help AI extract content.
Avoid hiding critical information in images or complex JavaScript, as AI may not process it efficiently.
Google Search Console adds branded vs. non-branded filter
Google Search Console now includes a filter to separate branded and non-branded queries. This helps brands identify confusion in search intent and optimize accordingly.
Why it matters: If non-branded queries drive traffic, it may signal an opportunity to refine messaging or target new audiences.
Actionable takeaway:
Use the filter to identify gaps in your content strategy (e.g., if branded queries dominate, expand into non-branded topics).
Monitor for unexpected branded queries, which may indicate confusion or misalignment with user intent.
Google Maps integrates AI for search
Google Maps is testing an AI-powered chat feature that lets users ask questions (e.g., “Find a Starbucks on my route”). Early feedback suggests it’s not yet as accurate as traditional search, but this could evolve quickly.
Why it matters: AI-driven local search could change how users discover businesses, making it critical to optimize for conversational queries.
Actionable takeaway:
Ensure your Google Business Profile is up to date with accurate hours, locations, and services.
Use natural language in your content to align with how users phrase questions.
Universal Commerce Protocol (UCP) expands
Google’s Universal Commerce Protocol (UCP), an open standard for AI-driven e-commerce, added new features like cart management, catalog search, and identity linking (for loyalty programs). This aims to streamline shopping within AI platforms.
Why it matters: UCP could become a standard for AI-powered commerce, making it essential for e-commerce brands to adopt early.
Actionable takeaway:
Explore UCP integration to improve visibility in AI-driven shopping experiences.
Optimize product schema and ensure your Merchant Center data is accurate.
Zero-click search doesn’t mean zero influence
Rand Fishkin’s keynote at the Industrial Marketing Summit highlighted that while zero-click searches are rising, brands can still influence AI responses by maintaining a strong, consistent presence across multiple platforms.
Why it matters: AI relies on corroborating signals (e.g., repeated mentions of your brand across trusted sources) to validate information. A single website isn’t enough, so you need a multi-channel strategy.
Actionable takeaway:
Repurpose content across platforms (e.g., LinkedIn, Substack, YouTube) to reinforce your brand’s authority.
Ensure your messaging is consistent across all channels to improve AI’s confidence in your content.
What to focus on in 2026
The March 2026 update highlighted several priorities for search strategy:
Optimize for AI-driven search: Use structured data, clear headings, and consistent messaging to improve visibility in AI responses.
Build brand authority across channels: Diversify your presence beyond your website to reinforce your narrative in AI-generated content.
Prepare for agentic commerce: Adopt protocols like UCP and optimize product schema for AI-powered shopping.
Avoid low-quality AI-generated content: Focus on high-value, human-centric content that aligns with user intent.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2026-03-27 09:02:132026-03-27 09:02:13The March 2026 SEO Update by Yoast recap
For years, SEO followed a fairly predictable playbook: create valuable content, optimize it for search engines, and compete for rankings on Google. But the way people discover information online is changing quickly. Tools like ChatGPT, Perplexity, and Gemini are introducing a new layer between users and search engines, where answers are generated and synthesized rather than simply retrieved.
In a recent episode of the Get Discovered podcast, Joe Walsh, CEO of Prerender.io, sat down with Yoast’s Principal Architect Alain Schlesser to discuss what this shift means for SEO and online discoverability. Their conversation explores how AI answer engines are reshaping the search landscape and why many traditional SEO assumptions no longer fully apply.
Alain shares insights on:
How AI systems retrieve and surface information
Why brands must rethink their online positioning, and
What businesses should start preparing for as AI-driven discovery evolves over the next 12–18 months?
The new discovery layer: AI is becoming the gatekeeper
“There’s now a layer in front of search that acts as a gatekeeper before you even hit those search engines.”
AI adds a new layer to the information discovery process for the searchers
That’s how Alain describes one of the biggest structural shifts happening in online discovery today. For years, the flow of search was straightforward: a user typed a search term into a search engine, the engine returned a list of results, and the user decided which link to click.
But AI-powered systems have added a new layer to that process.
From search queries to conversational discovery
Today, many users begin their search journey by asking questions in tools like ChatGPT, Perplexity, or Gemini instead of typing traditional keyword queries. The AI system then determines whether it needs external information and may generate multiple search queries behind the scenes to retrieve relevant sources.
The discovery flow now looks something like this:
The traditional vs the new agentic search
Previously:
User → Search engine → Website
Now:
User → AI model → Search engine → Website → AI synthesis → User
Instead of presenting a list of links, the AI model interprets and combines information before generating an answer. Alain explains this process in more detail in the podcast, highlighting how AI systems now act as a filtering layer between users and the web.
Search is fragmenting beyond Google
“We were in a rather comfortable position where we were only dealing with a monopoly search.”
For much of the past two decades, SEO largely meant optimizing for one ecosystem: Google. Even though other search engines existed, Google dominated how people discovered information online.
But that environment is changing.
As Alain explains, AI systems are introducing a new layer of fragmentation in discovery. Different AI platforms rely on different combinations of search engines, indexes, and training data, which means results can vary widely between them.
In practice, that means a brand might appear prominently in one AI system while barely showing up in another. For SEO teams, this marks a shift toward thinking about visibility across multiple AI-driven environments rather than just one search engine.
Despite technological changes, Alain emphasizes that the core principles of good SEO remain intact.
“You shouldn’t try to game the search engine. You need to create valuable content that humans actually want to read, and structure it so search engines can understand it.”
At its core, search still aims to deliver the best possible answers to users. Whether the request comes from a person typing a query or an AI model generating one behind the scenes, the goal remains the same: surface useful, reliable information.
That means SEO teams should continue focusing on fundamentals such as:
AI systems may change how information is surfaced, but they still rely on the same underlying signals of quality and relevance.
The “top results or nothing” reality
As the discovery landscape evolves, another important shift emerges in how AI systems interact with search results.
“They don’t see the full search result page. What the LLM typically sees is just the five topmost elements per search query.”
Unlike human users, AI systems typically work with a very small set of retrieved sources before generating an answer. That means if your content doesn’t appear among those top results, it may never reach the AI system at all.
In a world where AI answers rely on the summarization of modern content, only the sources that make it into that small retrieval window influence the final response.
This makes strong search visibility more important than ever. Ranking well isn’t just about earning clicks anymore. It determines whether your content is even considered when AI systems construct an answer.
Why “safe” content strategies are no longer enough
Even if your content reaches those top results, there’s another layer of filtering happening inside the AI model itself.
Large language models compress enormous amounts of information during training. As Alain explains:
What the model keeps are the dominant signal and the outliers. Everything in between is often compressed away as statistical noise.
In the podcast, Alain uses this idea to explain why brands that try to be broadly acceptable or “safe” may struggle to stand out in AI-driven discovery.
The takeaway is clear: in a world where AI systems summarize and compress information, having a clear and distinctive perspective becomes increasingly important.
Why Yoast launched AI visibility tracking
As AI systems reshape how information is discovered and summarized, a new challenge emerges for businesses: understanding how their brand appears in AI-generated answers. That’s the problem Yoast set out to address with Yoast SEO AI +, a feature designed to help businesses monitor how their brand shows up across major AI platforms.
Earlier in this article, we explored how AI systems now sit between users and search engines, retrieve only a small set of results, and synthesize answers through the summarization of modern content. Together, these changes create a new discovery layer that is far less transparent than traditional search.
As Alain explains in the podcast:
“We need more visibility and observability into that AI-based layer to figure out what is going on there. Right now, it’s mostly a black box.”
Unlike traditional search engines, AI systems don’t provide clear rankings, impressions, or click data that explain why a source was selected. Instead, answers are generated from a mix of retrieved content, training data, and model reasoning. For businesses, that makes it much harder to understand whether their brand is visible in AI-driven discovery.
This is where AI visibility tracking becomes valuable. Rather than focusing only on search rankings, teams also need insight into how their brand is represented inside AI responses.
Yoast SEO AI + helps surface that layer by allowing teams to observe how their brand appears across AI systems, such as ChatGPT, Perplexity, and Gemini.
The goal is not simply to track another metric. It’s to help businesses understand how AI systems interpret and represent their brand.
As Alain notes, visibility in AI systems can vary significantly depending on the platform, because each one relies on different combinations of:
search engines
indexes
training datasets
This means a brand might appear frequently in one AI system while barely showing up in another. Without visibility into those differences, it becomes difficult for teams to understand how their content performs in the new discovery landscape.
In that sense, tools like Yoast SEO AI + are less about selling a new SEO feature and more about helping businesses observe a rapidly changing ecosystem where discoverability no longer happens only in search results.
The next evolution: AI agents making decisions
“What we will increasingly see is automated transactions where AI agents navigate websites and initiate actions on behalf of users.”
So far, much of the discussion around AI and search has focused on how answers are generated. But according to Alain, the next phase of this evolution may go further.
Over the next 12–18 months, AI systems may begin moving beyond answering questions and start performing tasks on behalf of users. Instead of guiding someone toward a website to make a decision, AI agents could increasingly compare options, interact with websites, and complete actions automatically.
If that shift happens, the traditional customer journey could change significantly. Alain shares a fascinating perspective on what this might mean for businesses in the coming years in the full podcast conversation.
SEO matters more than ever
AI isn’t replacing SEO. If anything, it’s reinforcing why good SEO matters in the first place. What’s changing is the path between users and content. Instead of navigating search results themselves, users increasingly receive answers that AI systems retrieve, interpret, and synthesize.
That makes strong fundamentals more important than ever. Businesses still need to focus on:
valuable content
clear structure
discoverable and indexable pages
a distinctive brand identity
But the central question for SEO is evolving. It’s no longer just:
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2026-03-13 12:32:092026-03-13 12:32:09Rethinking SEO in the age of AI
A good XML sitemap serves as a roadmap for your website, guiding Google to all your important pages. XML sitemaps can be beneficial for SEO, helping Google find your essential pages quickly, even if your internal linking isn’t perfect. This post explains what they are and how they help you rank better and get surfaced by AI agents.
An XML sitemap is crucial for SEO, as it guides search engines to your important pages, improving crawl efficiency
XML sitemaps list essential URLs and provide metadata, helping search engines understand content and prioritize crawling
With Yoast SEO, you can automatically generate and manage XML sitemaps, keeping them up to date
XML sitemaps support faster indexing of new content and help discover orphan pages that aren’t linked elsewhere
Add your XML sitemap to Google Search Console to help Google find it quickly and monitor indexing status
What are XML sitemaps?
An XML sitemap is a file that lists a website’s essential pages, ensuring Google can find and crawl them. It also helps search engines understand your website structure and prioritize important content.
Fun fact:
XML is not the only type of sitemap; there are several sitemap formats, each serving a slightly different purpose:
RSS, mRSS, and Atom 1.0 feeds: These are typically used for content that changes frequently, such as blogs or news sites. They automatically highlight recently updated content
Text sitemaps: The simplest format. These contain a plain list of URLs, one per line, without additional metadata
These are HTML sitemaps that are created for visitors, not search engines. They list and link to important pages in a clear, hierarchical structure to improve user navigation. An XML sitemap, however, is specifically designed for search engines.
XML sitemaps include additional metadata about each URL, helping search engines better understand your content. For example, it can indicate:
When a page was last meaningfully updated
How important is a URL relative to other URLs
Whether the page includes images or videos, using sitemap extensions
Search engines use this information to crawl your site more intelligently and efficiently, especially if your website is large, new, or has complex navigation.
Looking to expand your knowledge of technical SEO? We have a course in the Yoast SEO Academy focusing on crawlability and indexability. One of the topics we tackle is how to use XML sitemaps properly.
What does an XML sitemap look like?
An XML sitemap follows a standardized format. It is a text file written in Extensible Markup Language (XML) that search engines can easily read and process. As it follows a structured format, search engines like Google can quickly understand which URLs exist on your website and when they were last updated.
Here is a very simple example of an XML sitemap that contains a single URL:
Each URL in a sitemap is wrapped in specific XML tags that provide information about that page. Some of these tags are required, while others are optional but helpful for search engines.
Below is a breakdown of the most common XML sitemap tags:
Tag
Requirement
Description
<?xml>
Mandatory
Declares the XML version and character encoding used in the file.
<urlset>
Mandatory
The container for the entire sitemap. It defines the sitemap protocol and holds all listed URLs.
<url>
Mandatory
Represents a single URL entry in the sitemap. Each page must be enclosed within its own <url> tag.
<loc>
Mandatory
Specifies the full canonical URL of the page you want search engines to crawl and index.
<lastmod>
Optional
Indicates the date when the page was last meaningfully updated, helping search engines know when to re-crawl the page.
<changefreq>
Optional
Suggests how frequently the content on the page is expected to change, such as daily, weekly, or monthly.
<priority>
Optional
Suggests the relative importance of a page compared to other pages on the same site, using a scale from 0.0 to 1.0.
Note: While sitemaps.org supports optional tags like <changefreq> and <priority>, Google and Bing generally ignore them. Google has officially discarded them. Instead, it prefers <lastmod> to signal (last modified) when content actually updates.
What is an XML sitemap index?
A sitemap index is a file that lists multiple XML sitemap files. Instead of containing individual page URLs, it acts as a directory that points search engines to several separate sitemaps.
This becomes useful when a website has a large number of URLs or when the site owner wants to organize sitemaps by content type. For example, a site may have separate sitemaps for pages, blog posts, products, or categories.
Here’s a breakdown of how XML sitemap and XML sitemap index differ:
Feature
XML Sitemap
XML Sitemap Index
Purpose
Lists individual URLs on a website
Lists multiple sitemap files
Content
Contains page URLs and optional metadata
Contains links to sitemap files
Use case
Suitable for small or medium-sized sites
Useful when a site has multiple sitemaps
Structure
Uses <urlset> and <url> tags
Uses <sitemapindex> and <sitemap> tags.
Search engines support sitemap limits. A single sitemap can contain up to 50,000 URLs or be up to 50 MB in size. If your website exceeds these limits, you can create multiple sitemaps and group them together using a sitemap index.
Submitting a sitemap index to search engines allows them to discover and process all your sitemaps from a single file.
In short, an XML sitemap helps search engines discover pages, while a sitemap index helps search engines discover multiple sitemaps.
Below is a simple example of what a sitemap index file looks like:
In this example, the sitemap index references two separate sitemaps. Each one can contain thousands of URLs. This structure helps search engines efficiently discover and crawl large websites.
Why do you need an XML sitemap?
Technically, you don’t need an XML sitemap. Search engines can often discover your pages through internal links and backlinks from other websites. However, having an XML sitemap is highly recommended because it helps search engines crawl and understand your site more efficiently.
Here are some key benefits of using an XML sitemap:
Improved crawl efficiency
Sitemaps help search engines like Google and Bing crawl large or complex websites more efficiently. By listing your important URLs in one place, you make it easier for crawlers to find and prioritize valuable pages.
Faster indexing of new content
When you update or add new pages to your site, including them in your sitemap helps search engines discover them sooner. This can lead to faster indexing, especially for websites that publish content frequently, such as blogs, news sites, or e-commerce stores with changing product listings.
Discovery of orphan pages
Orphan pages are pages that are not linked from other parts of your website. Because crawlers typically follow links to discover content, these pages can sometimes be missed. An XML sitemap can help ensure these pages are still discovered.
Additional metadata signals
XML sitemaps can include additional metadata about each URL, such as the <lastmod> tag. This information helps search engines understand when a page was last updated and whether it may need to be crawled again.
Support for specialized content
Sitemaps can also be extended to include specific types of content, such as images or videos. These specialized sitemaps help search engines better understand and surface media content in results like Google Images or video search.
Better understanding of site structure
A well-organized sitemap gives search engines a clearer overview of your website’s structure and the relationship between different sections or content types.
Indexing insights through Search Console
When you submit your sitemap to tools like Google Search Console, you can monitor how many URLs are discovered and indexed. This also helps you identify crawl issues or indexing errors.
Support for multilingual websites
For websites targeting multiple languages or regions, XML sitemaps can include alternate language versions of pages using hreflang annotations. This helps search engines serve the correct language version to users in different locations.
Do XML sitemaps matter for AI search?
Yes, but indirectly. AI-powered search experiences like AI Overviews or Bing Copilot still rely on the traditional search index to discover and retrieve content. That means your pages usually need to be crawled and indexed first before they can appear in AI-generated answers.
This is where XML sitemaps still help. By listing your important URLs in one place, a sitemap makes it easier for search engines to discover and index your content. Keeping the <lastmod> value accurate can also help search engines prioritize recently updated pages, which is especially useful for AI systems that aim to surface fresh information.
In short, a sitemap won’t make your content appear in AI answers by itself. But it helps ensure your pages are discoverable, indexed, and up to date, which increases their chances of being used in AI-powered search results.
Adding XML sitemaps to your site with Yoast
Because XML sitemaps play an important role in helping search engines discover and crawl your content, Yoast SEO automatically generates XML sitemaps for your website. This feature is available in both the free and premium versions (Yoast SEO Premium, Yoast WooCommerce SEO, and Yoast SEO AI+) of the plugin.
A smarter analysis in Yoast SEO Premium
Yoast SEO Premium has a smart content analysis that helps you take your content to the next level!
Instead of requiring you to manually create or maintain sitemap files, Yoast SEO handles everything automatically. As you publish, update, or remove content, the plugin updates your sitemap index and the individual sitemaps in real time. This ensures search engines always have an up-to-date overview of the pages you want them to crawl and index.
Yoast SEO also organizes your sitemaps intelligently. Rather than placing every URL in a single file, the plugin creates a sitemap index that groups separate sitemaps for different content types, such as posts, pages, and other public content types, with just one click.
Another important advantage is that Yoast SEO only includes content that should actually appear in search results. Pages set to noindex are automatically excluded from the XML sitemap. This helps keep your sitemap clean and focused on the URLs that matter for SEO.
Controlling what appears in your sitemap
While the plugin automatically manages sitemaps, you still have full control over which content is included.
For example, if you don’t want a specific post or page to appear in search results, you can change the setting “Allow search engines to show this content in search results?” in the Yoast SEO sidebar under the Advanced tab. When this option is set to No, the content will be marked as noindex and automatically excluded from the XML sitemap. When set to Yes, the content remains eligible to appear in search results and is included in the sitemap.
This makes it easy to keep your sitemap focused on the pages you actually want search engines to crawl and index. In some cases, developers can further customize sitemap behavior. For example, filters can be used to limit the number of URLs per sitemap or to programmatically exclude certain content types.
Because all of this happens automatically, most website owners never need to manage sitemap files manually. Yoast SEO keeps your XML sitemap clean, up to date, and optimized for search engines as your site grows.
If you want Google to find your XML sitemap quicker, you’ll need to add it to your Google Search Console account. You can find your sitemaps in the ‘Sitemaps’ section. If not, you can add your sitemap at the top of the page.
Adding your sitemap helps check whether Google has indexed all pages in it. We recommend investigating this further if there is a significant difference between the ‘submitted’ and ‘indexed’ counts for a particular sitemap. Maybe there’s an error that prevents some pages from indexing? Another option is to add more links pointing to content that has not yet been indexed.
Google correctly processed all URLs in a post sitemap
What websites need an XML sitemap?
Google’s documentation says sitemaps are beneficial for “really large websites,” “websites with large archives,” “new websites with just a few external links to them,” and “websites which use rich media content.” According to Google, proper internal linking should allow it to find all your content easily. Unfortunately, many sites do not properly link their content logically.
While we agree that these websites will benefit the most from having one, at Yoast, we think XML sitemaps benefit every website. As the web grows, it’s getting harder and harder to index sites properly. That’s why you should provide search engines with every available option to have it found. In addition, XML sitemaps make search engine crawling more efficient.
Every website needs Google to find essential pages easily and know when they were last updated. That’s why this feature is included in the Yoast SEO plugin.
Which pages should be in your XML sitemap?
How do you decide which pages to include in your XML sitemap? Always start by thinking of the relevance of a URL: when a visitor lands on a particular URL, is it a good result? Do you want visitors to land on that URL? If not, it probably shouldn’t be in it. However, if you don’t want that URL to appear in the search results, you must add a ‘noindex’ tag. Leaving it out of your sitemap doesn’t mean Google won’t index the URL. If Google can find it by following links, Google can index the URL.
Example: A new blog
For example, you are starting a new blog. Of course, you want to ensure your target audience can find your blog posts in the search results. So, it’s a good idea to immediately include your posts in your XML sitemap. It’s safe to assume that most of your pages will also be relevant results for your visitors. However, a thank you page that people will see after they’ve subscribed to your newsletter is not something you want to appear in the search results. In this case, you don’t want to exclude all pages from your sitemap, only this one.
Let’s stay with the example of the new blog. In addition to your blog posts, you create some categories and tags. These categories and tags will have archive pages that list all posts in that specific category or tag. However, initially, there might not be enough content to fill these archive pages, making them ‘thin content’.
For example, tag archives that show just one post are not that valuable to visitors yet. You can exclude them from the sitemap when starting your blog and include them once you have enough posts. You can even exclude all your tag pages or category pages simultaneously using Yoast SEO.
However, this kind of page could also be excellent ranking material. So, if you think: well, yes, this tag page is a bit ‘thin’ right now, but it could be a great landing page, then enrich it with additional information and images. And don’t exclude it from your sitemap in this case.
Frequently asked questions about XML sitemaps
There are a lot of questions regarding XML sitemaps, so we’ve answered a couple in the FAQ below:
What happens when Google Search Console says an XML sitemap has errors?
An invalid or improperly read XML sitemap usually indicates a specific error that needs investigation. Check the reported issue to understand what is causing the problem. Make sure the sitemap has been submitted through the search engine’s webmaster tools. When the sitemap is marked as invalid, review the listed errors and apply the appropriate fixes for each one.
How can I check whether a website has an XML sitemap?
In most cases, you can find out if sites have an XML sitemap by adding sitemap.xml to the root domain. So, that would be example.com/sitemap.xml. If a site has Yoast SEO installed, you’ll notice that it’s redirected to example.com/sitemap_index.xml. sitemap_index.xml is the base sitemap that collects all the sitemaps on your site into a single page.
How can I update an XML sitemap?
There are ways to create and update your sitemaps by hand, but you shouldn’t. Also, there are static generators that let you generate a sitemap whenever you want. But, again, this process would need to repeat itself every time you add or update content. The best way to do this is by simply using Yoast SEO. Turn on the XML sitemap in Yoast SEO, and all your updates will be applied automatically.
Can I use <priority> in my XML sitemap?
In the past, people believed that adding the <priority> attribute to sitemaps would signal to Google that specific URLs should be prioritized. Unfortunately, it doesn’t do anything, as Google has often said it doesn’t use this attribute to read or prioritize content in sitemaps.
Check your own XML sitemap!
Now you know how important it is to have an XML sitemap: it can help your site’s SEO. If you add the correct URLs, Google can easily access your most important pages and posts. Google will also find updated content easily, so it knows when a URL needs to be crawled again. Lastly, adding your XML sitemap to Google Search Console helps Google find it quickly and lets you check for sitemap errors.
So check your XML sitemap and find out if you’re doing it right!
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Version 4.6 of Yoast Duplicate Post is here, and it’s all about making your editing experience feel more natural in WordPress’s Block Editor, and making sure “Rewrite & Republish” works reliably every time you need it.
A more modern editing experience
Everything where you’d expect it. The Duplicate Post controls now sit in the Block Editor’s sidebar, right alongside WordPress’s own settings, no more hunting around. If you’re still on the Classic Editor, nothing changes for you.
Buttons that look the part. The “Copy to a new draft” and “Rewrite & Republish” actions are now proper bordered buttons, consistent with the rest of the WordPress interface. Cleaner, clearer, and easier to use.
Built for the future. Under the hood improvements ensure Duplicate Post stays stable and compatible as WordPress continues to evolve, so you don’t have to think about it.
Yoast Duplicate Post has always been about reliability. While the plugin has served millions of you faithfully since our last release, we’re excited to bring you version 4.6. This update is packed with long-awaited fixes and thoughtful interface refinements that ensure the plugin stays modern, stable, and ready for the future of WordPress.
Enrico Battocchi – Plugin team lead and creator of Duplicate Post
More reliable “Rewrite & Republish” workflows
Your posts won’t get stuck. If something goes wrong mid-process, like a redirect being interrupted, the plugin now handles it gracefully and cleans up automatically. Your content will never be left in a stuck state.
Attachments copied completely. All attachment metadata, including captions and descriptions, is fully preserved when you duplicate a post. Nothing gets left behind.
International & security improvements
The right words, in your language. Buttons and notices in the Block Editor are now correctly translated across all languages, with none of the behind-the-scenes errors that some locales were seeing.
Consistent styling, always. Buttons display correctly regardless of your admin configuration, including when the WordPress admin bar is turned off.
Version 4.6 is available now. As always, we recommend testing in a staging environment before updating your live site.
Imagine a web ecosystem where not just humans but AI agents communicate with websites, going beyond traditional browsing. Unlike conventional web experiences, where people click, scroll, and search, AI agents can navigate, interpret, and even perform tasks autonomously on your site. This is not a futuristic concept. It is already unfolding. This is the emergence of the agentic web.
The agentic web enables AI agents to autonomously navigate and interact with websites, shifting user responsibilities from manual navigation to decision-making
Protocols are crucial for communication among AI agents; they must rely on structured, machine-readable data for effective coordination
SEO professionals must adapt to the agentic web by optimizing websites as endpoints for AI queries, ensuring structured data and clarity
NLWeb facilitates interaction between agents and websites by exposing structured data and allowing for natural language queries without traditional interface limitations
Yoast’s collaboration with NLWeb helps WordPress users prepare for the agentic web by organizing content and making it easier to integrate structured data
The big shift: From web for users to a web for users and agents
For years, the web followed a simple pattern. Humans searched, clicked, compared, and completed tasks manually. Even as search engines evolved, the interaction model stayed the same: search and click.
That model is changing.
The agentic web represents a shift from a web designed only for human users to one designed for both people and AI assistants. Instead of manually researching products, comparing services, filling out forms, and completing transactions, users will increasingly delegate those tasks to intelligent assistants that can search, interpret information, and act on their behalf. The user’s role shifts from active navigator to decision-maker.
From searching to delegating.
This is not about smarter chat interfaces. It is about autonomous agents that can interpret the search intent, compare options, and execute actions on behalf of users. Websites are no longer just pages to be visited. They are endpoints to be queried.
For that to work at scale, intelligence cannot reside in a single assistant or on a closed platform. It has to be distributed. Systems must be able to communicate with other systems without friction. That requires a web that is machine-readable, interoperable, and built for agent-to-agent interaction.
The agentic web is not a prediction. It is an architectural shift already underway!
Protocol thinking and the infrastructure of agentic web communication
If the agentic web is about intelligent systems interacting with websites, then the real question becomes simple: how do these systems understand each other?
The answer is not design. It is infrastructure.
The web has always depended on shared communication rules. HTTP allows browsers to request pages. RSS distributes updates. Structured data helps search engines interpret meaning. These are not features. They are protocols. They are agreements that enable large-scale coordination.
Now the same logic applies to AI agents.
In the agentic web, agents will not click buttons or visually scan pages. They will send requests, interpret structured responses, compare options, and complete tasks. For that to work across millions of websites, communication cannot be improvised. It must be standardized.
This is where protocol thinking becomes essential.
Protocol thinking means designing websites so they are predictable for machines. Instead of building custom integrations for every assistant or platform, websites expose a consistent interaction layer. Agents do not need to learn every interface. They rely on shared rules.
As emphasized in discussions of distributed intelligence, the goal is not to let a single chatbot control everything. The intelligence must be distributed. Systems need a simplified way to communicate without having to understand the technical details of every tool they connect to.
That only works when there is common ground.
In practical terms, this means:
Websites must expose structured, machine-readable data
Agents must know what they can ask
Responses must follow predictable formats
Communication must scale beyond one platform
Protocols create that shared language.
What does this mean for SEO professionals?
As the web evolves to support AI agents, SEO professionals are starting to ask a new question: how do you stay visible when answers are generated instead of ranked?
A clear example of this surfaced during Microsoft’s Ignite event. In a Q&A session, a consultant described a client who sells products like mayonnaise and wanted their brand to appear when someone asks an AI assistant about mayonnaise. The question was simple, but it revealed something deeper. If AI systems generate answers instead of listing search results, what does optimization look like?
This is where the shift becomes real.
The agentic web does not replace the open web. It adds another layer on top of it. Search engines still index pages. Rankings still matter. But intelligent systems can now query websites directly, compare information across sources, and generate synthesized responses.
For SEOs, this changes the website’s role.
It is no longer enough to think in terms of pages to be visited. Websites must be treated as endpoints to be queried.
This means structured data, clean information architecture, and machine-readable content are not just enhancements for rich results. They are the foundation that allows AI systems to interpret and select your content in the first place.
The agentic web is an additional layer on the open web, not a replacement for it. To stay visible, SEO professionals must ensure their websites are structured, accessible, and ready to be queried by intelligent systems.
Visibility in this new layer depends on clarity, interoperability, and infrastructure.
NLWeb was first introduced by Microsoft in May 2025 as an open project designed to make it simple for websites to offer rich natural language interfaces using their own data and model of choice. Later, in November at Microsoft Ignite, Microsoft presented NLWeb again alongside its first enterprise offering through Microsoft Foundry.
At its core, NLWeb aims to make it easy for a website to function like an AI app. Instead of navigating pages manually, users and agents can query a site’s content directly using natural language.
But NLWeb is more than just a conversational layer.
Every NLWeb instance is also a Model Context Protocol, or MCP, server. This means that when a website enables NLWeb, it becomes inherently discoverable and accessible to agents operating within the MCP ecosystem. In simple terms, agents do not need custom integrations for every site. If a website supports NLWeb, agents can recognize it and interact with it in a standardized way.
NLWeb is a conversational layer that interacts with a website and retrieves information
NLWeb builds on formats that websites already use, such as Schema.org and RSS. It combines that structured data with large language models to generate natural language responses. This allows websites to expose their content in a way that both humans and AI agents can understand.
Importantly, NLWeb is technology agnostic. Site owners can choose their preferred infrastructure, models, and databases. The goal is interoperability, not platform lock-in.
In many ways, NLWeb is positioned to play a role in the agentic web similar to what HTML did for the early web. It provides a shared communication layer that allows agents to query websites directly, without relying only on traditional crawling or visual interfaces.
How is NLWeb different from standard LLM citations?
With standard LLM citations, the model generates an answer first, then adds sources. The response is still probabilistic, which can introduce inaccuracies or hallucinations.
NLWeb works differently.
It treats the language model as a smart retrieval layer. Instead of inventing answers, it pulls verified objects directly from the website’s structured data and presents them in natural language.
That distinction matters. It means responses are grounded in the publisher’s own data from the start, reducing the risk of hallucination and giving site owners greater control over how their content is represented.
What NLWeb means for the agentic web
The agentic web depends on systems being able to communicate at scale. Agents cannot manually interpret every interface or navigate every page visually. They need structured, machine-readable access.
NLWeb helps enable that.
Instead of requiring custom integrations for every assistant or platform, a website can expose an NLWeb-enabled endpoint. Agents only need to know that a site supports NLWeb. The protocol handles how requests are made and how responses are structured.
This supports a more distributed ecosystem. The goal is not to let one chatbot control everything. Intelligence must be distributed across the web.
Generative interfaces do not replace content. They depend on well-structured, accessible content. When an AI system summarizes results or compares options, it is still drawing from the information that websites provide. NLWeb simply creates a clearer path for that interaction.
Yoast’s collaboration with NLWeb and what it means for WordPress users
As part of the NLWeb announcement, Microsoft highlighted Yoast as a partner helping bring agentic search capabilities to WordPress. You can read more about this collaboration in our official press announcement on Yoast and Microsoft’s NLWeb integration.
For many WordPress site owners, concepts like infrastructure, endpoints, and protocols can feel abstract. That is exactly where preparation matters.
While Yoast does not automatically deploy NLWeb for users, the schema aggregation feature in Yoast SEO, Yoast SEO Premium, Yoast WooCommerce SEO, and Yoast SEO AI+ organizes and structures content, making it significantly easier to build NLWeb. When site owners enable the relevant Yoast feature, nothing changes visually on the front end. What changes is the underlying structure.
In short, we map and organize structured data to reduce the technical effort required to build NLWeb on top of it. In other words, we help publishers complete much of the groundwork.
The agentic web is not about chasing a trend. It is about ensuring your content remains discoverable, understandable, and usable in a world where intelligent systems increasingly act on behalf of users.
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In November 2025, Yoast announced a collaboration with NLWeb, an open web protocol developed by Microsoft designed to simplify building conversational interfaces for the web.
Today, we are proud to introduce the first major result of that work: Yoast SEO Schema Aggregation. This is an opt in feature that brings your website’s structured data together in a clearer and more consistent way. By choosing to enable it, you can help search engines and intelligent agents better understand and use your content.
If you want to see which schema types are available for your WordPress setup, our schema overview explains what is included across different product plans.
Bridging the gap: from discovery to conversation
Yoast has a history of helping WordPress websites be represented fairly and responsibly in the open web.
Today: we are taking the next step. As the agentic web becomes more important, we are helping your WordPress site move from being discovered to being understood and engaged with through conversation.
Starting today, the new Schema Aggregation feature in Yoast SEO is here. It establishes a standardized connection between your website’s structured data and the systems that power AI-driven discovery and interaction. These include large language models, agents, and conversational assistants such as Copilot. It helps ensure your published content can be understood correctly by AI. This matters as AI becomes part of how people find and use information online.
The NLWeb + Yoast integration is built in collaboration with the NLWeb team, including R.V. Guha, co-founder of Schema.org. Together, we are extending the open web standards you already rely on, so your WordPress website can participate confidently in the emerging agentic web in a responsible and future ready way.
Benefits of the Schema Aggregation feature
Questions about AI often come down to one thing: who can access your data. This feature is built with a privacy first approach from the start.
Complete: All indexable content included
Clean: No duplicate entities, no navigation clutter
Connected: Relationships between entities preserved (author → articles)
Compliant: Respects exisiting privacy settings
Fast: Sub-100ms cached responses, pagination for large sites
For developers and technical users who want more control, we have developer documentation on schema markup. It explains how to inspect and extend your schema graph. This gives you maximum personalization, while retaining standardization at scale.
“You can’t stop the AI wave, but you can direct it. Our integration with NLWeb puts you back in charge. It allows you to manage server load efficiently and ensures that when AIs do access your content, they get the rich, semantic understanding necessary to represent you correctly.” Alain Schlesser – Principal Architect, Yoast.
What’s new
The next time you log in and open Yoast SEO (updated to 27.1), you’ll see a short guided walkthrough. It introduces the new Schema Aggregation feature. It also shows how to enable it using a simple toggle.
We have added a new endpoint to Yoast SEO (free), making the Schema Aggregation feature available to all customers who choose to enable it. The endpoint exposes your site’s full structured data graph in a proposed new standard called a schemamap.
That means, instead of an AI system crawling hundreds of pages individually (or however many pages you have on your website), it can now retrieve your site’s schema, including articles, authors, products, and organizational data, in one optimized request.
Before and after: from pages to a connected site
Below is an example of the structured data Yoast already outputs on an individual page. This page level schema helps search engines understand what that specific page is about, including its content type, author, and relationships.
An example of Yoast schema markup at the individual page level, the example shown is yoast.com
With Schema Aggregation enabled, Yoast provides a site-level view. Instead of looking at pages in isolation, your entire website’s structured data is connected. It consolidates into a single output called a schemamap. This can appear quite overwhelming to look at. It makes it easier for AI systems to understand your content. They can see how your articles, authors, products, and organisation relate to each other across the site.
How it works: Standardized, connected, and deduplicated
The Schema Aggregation feature doesn’t just share data; it organizes it for AI consumption:
Eliminates data mess: It merges duplicate mentions of authors, products, or articles into one scalable, connected record.
Integrates automatically: If you use one of our Schema API partners like The Events Calendar or WP Recipe Maker, those schema types are included in the graph automatically.
Developers can also explore our Schema Integrations page to see how Schema API partners connect to and extend the Yoast SEO Schema Framework (the graph).
Collaborative innovation
When working at scale across tens of millions of websites, careful testing is essential to ensure a safe and reliable launch. This feature was developed with agencies and advanced users in mind, and tested in controlled environments.
We collaborated closely with Syde, our Innovation Partner, to test the new feature across a diverse range of real-world client scenarios. The approach for this release was tested in controlled environments to confirm scalability and consistent output quality before deployment.
Syde’s feedback has been instrumental in refining the schema aggregation logic. We look forward to continuing this partnership, working together to help clients remain visible and accurately represented as AI driven systems evolve.
Be visible, understood, and represented
The rules of discovery are shifting, but your site doesn’t have to be left behind. With NLWeb and Yoast, your website stays at the center of the conversation.
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The February 2026 SEO Update by Yoast is part of our monthly webinar series covering the latest developments in search and AI. In each session, we review the most important news from the past month and explore how it affects your search strategy.
Hosted by Carolyn Shelby and Alex Moss, this month’s update focused on AI-driven shifts in search, emerging agentic workflows, and Google’s latest core updates. Below is a recap of the topics discussed and what they mean for your strategy.
Watch the full recap on YouTube to hear Carolyn and Alex dive deeper into these topics, answer audience questions, and share real-world examples.
SEO and AI news from February 2026
Search engines expand AI reporting and website controls
Google and Bing introduced new tools for publishers to manage AI interactions. Bing’s AI Performance Report shows how often Copilot cites your site, including citation counts and queries. Google now allows publishers to control AI access via robots.txt using Google-Extended.
Actionable takeaway:
Monitor AI citation reports in Bing Webmaster Tools to track visibility
Review your robots.txt and AI access settings to align with your strategy
Debate over Markdown, AI agents, and machine-readable content
Simplify your site’s structure to make content more accessible to AI agents
If your site is overly complex, explore Markdown or structured data alternatives, but prioritize fixing underlying issues first
Is Google cracking down on self-promotional listicles?
Lily Ray identified a pattern of sites losing visibility due to self-promotional listicles (e.g., “Top 20 SEO Agencies in the US,” with the publisher ranked #1). Google appears to be penalizing manipulative tactics.
Actionable takeaway:
Avoid self-serving listicles. If creating comparison content, use objective criteria and transparent methodology
Microsoft’s vision for a sustainable agentic web
Microsoft outlined its approach to agentic search, emphasizing structured data, concise content, and publisher compensation for AI-driven traffic. The shift from human clicks to AI-driven retrieval was highlighted as a major trend.
Actionable takeaway:
Optimize for machine-readable actions (e.g., structured data, clear CTAs)
Prepare for AI-driven monetization models (e.g., compensation for citations)
Meta’s Avacado agent and OpenClaw integration
Meta is testing Avacado, a new AI agent integrating OpenClaw and Manus for workflow automation. This reflects a broader push toward omnichannel AI interactions.
Actionable takeaway:
Ensure consistent messaging across all platforms (website, social, email) to reinforce AI comprehension
ChatGPT rolls out ads
ChatGPT began serving ads to free users, with OpenAI charging advertisers based on ad impressions rather than clicks. The move mirrors traditional search ad models but raises concerns about user experience.
Actionable takeaway:
Monitor how AI-driven ad placements impact user engagement and brand visibility
WebMCP is a new protocol for AI agents
Chrome introduced WebMCP, a protocol that enables AI agents to interact with websites via machine-readable actions (e.g., form submissions). Early adoption is limited, but it signals a shift toward agent-first web design.
Actionable takeaway:
Audit your site’s underlying code for clarity (e.g., semantic HTML, structured data)
Proceed cautiously. WebMCP is experimental and could pose security risks if misconfigured
Bing Webmaster Tools launches AI Performance Report
Bing’s AI Performance Report now shows how often Copilot cites your site, including queries and cited pages. The tool bridges traditional SEO metrics with AI-driven search.
Actionable takeaway:
Set up Bing Webmaster Tools if you haven’t already
Compare Bing’s AI data with Google Search Console to identify gaps
Google AI Mode introduces UCP-powered checkout
Google’s AI mode now supports UCP-powered checkout, allowing agents to complete purchases on behalf of users. Early adopters include Etsy, Wayfair, and Walmart.
Actionable takeaway:
If you’re in e-commerce, prioritize structured product data and fast load times to capitalize on agentic commerce
OpenClaw, OpenAI, and the future of AI agents
The rise of OpenClaw and OpenAI’s advancements underscores a shift toward websites exposing capabilities (not just pages) to AI agents. Early experiments show agents interacting with sites via machine-readable actions.
Actionable takeaway:
Focus on clear site structure and consistent data to ensure reliable AI interpretation
What to focus on in 2026
The February SEO Update by Yoast highlighted four key priorities:
Optimize for AI-driven search: Use structured data and markdown to improve AI comprehension
Build brand authority across channels: Ensure consistent messaging for AI agents to reinforce
Prepare for agentic commerce: Prioritize structured product data and fast load times
Avoid low-quality AI content: Google is cracking down on manipulative tactics like self-promotional listicles
Sign up for the next SEO Update by Yoast
The next SEO Update by Yoast is on March 24, 2026, at 4 PM CET / 10 AM EST. Sign up here to join the live discussion or receive the recording.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2026-02-26 16:10:272026-02-26 16:10:27Recap of the February 2026 SEO Update by Yoast
It is no secret that publishing SEO-friendly blog posts is one of the easiest and most effective ways to drive organic traffic and improve SERP rankings. However, in the era of artificial intelligence, blog posts matter more than ever. They help establish brand authority by consistently delivering fresh, valuable content that can be cited in AI-generated answers.
In this guide, we will share a practical, detailed approach to writing SEO-friendly blog content that not only ranks on Google SERPs but is also surfaced by AI models.
SEO friendly blog post now means writing with search intent, ensuring content is clear and quotable for AI systems
Key factors for SEO friendly blog posts include trustworthiness, machine-readability, answer-first structure, and topical authority
Conduct thorough keyword research and find readers’ questions to match search intent effectively
Use clear headings, improve readability, include inclusive language, and add relevant media to engage readers
Write compelling meta titles and descriptions, link to existing content, and focus on building authority to enhance visibility
What does an SEO-friendly blog post mean in the AI era?
The way people search for information has changed, and with it, the meaning of an SEO-friendly blog post. Before the rise of generative AI, writing an SEO-friendly blog post mostly meant this:
‘Writing content with the intention of ranking highly in search engine results pages (SERPs). The content is optimized for specific target keywords, easy to read, and provides value to the reader.’
That definition is not wrong. But it is no longer complete.
In the AI era, an SEO-friendly blog post is written with search intent first, answering a user’s question clearly and efficiently. It is not just about placing keywords in the right spots. It is about creating an information-dense piece with accurate, well-structured, and quotable sentences that AI systems can confidently extract and surface as direct answers.
The new definition clearly shows that strong SEO foundations still matter, and they matter more than ever. What has changed is how content is evaluated and discovered. Search engines and AI models now look beyond clicks and rankings to understand whether your content is trustworthy, helpful, and easy to interpret.
Here are some key factors that play a key role in determining whether a blog post is truly SEO-friendly:
Trustworthiness (E-E-A-T): Demonstrating real-world experience, expertise, and credibility helps your content stand out from low-value AI-generated rehashes
Machine-readability: Clear structure, clean HTML, and technical signals such as schema markup help search engines and AI systems understand what your content is about
Answer-first structure: Placing concise, direct answers at the beginning of sections makes it easier for AI models to extract and reference your content
Topical authority: Publishing interconnected, in-depth content around a subject is far more effective than creating isolated blog posts
9 tips to write SEO-friendly blogs for LLM and SERP visibility
Now we get to the core of this guide. Below are some foundational tips to help you plan and write SEO-friendly blog posts that are genuinely helpful, easy to understand, and focused on solving real reader problems. When done right, these practices not only improve search visibility but also shape how your brand is perceived by both users and AI systems.
1. Conduct thorough keyword research
Before you start writing a single word, start with solid keyword research. This step helps you understand how people search for a topic, which terms carry demand, and how competitive those searches are. It also ensures your content aligns with real user intent instead of assumptions.
You can use tools like Google Keyword Planner, Ahrefs, or Semrush for this. Personally, I prefer using Semrush’s Keyword Magic Tool because it quickly surfaces thousands of relevant keyword ideas around a single topic.
Keyword Magic Tool by Semrush for the relevant keyword list
Here’s how I usually approach it. I enter a broad keyword related to my topic, for example, ‘SEO.’ The tool then returns an extensive list of related keywords along with important metrics. I mainly focus on three of them:
Search intent, to understand what the user is really looking for
Keyword Difficulty (KD%), to estimate how hard it is to rank
Search volume, to gauge demand
This combination helps me choose keywords that are realistic to rank for and meaningful for readers.
If you use Yoast SEO, this process becomes even easier. Semrush is integrated into Yoast SEO (both free and Premium), giving you keyword suggestions directly in Yoast SEO. With a single click, you can access relevant keyword data while writing, making it easier to create focused, useful content from the start.
Keyword research tells you what people search for. Questions tell you why they search.
When you actively look for the questions your audience is asking, you move closer to matching search intent. This is especially important in the AI era, where search engines and AI models prioritize clear, answer-driven content.
For example, consider these two queries:
What are the key features of good running shoes?
This shows informational intent. The searcher wants to understand what makes a running shoe good.
What are the best running shoes?
This suggests a transactional or commercial intent. The searcher is likely comparing options before making a purchase.
Both questions are valid, but they require very different content approaches.
There are two simple ways I usually find relevant questions. The first is by checking the People also ask section in Google search results. By typing in a broad keyphrase, you can see related questions that Google itself considers relevant.
The People also ask section showing questions related to the broad keyphrase ‘SEO’
The second method is to use the Questions filter in Semrush’s Keyword Magic Tool. This helps uncover question-based queries directly tied to your main topic.
Apart from these methods, I also like using Google’s AI Overview and AI mode as a quick research layer. When I search for my main topic, I pay close attention to AI-cited sources, as they often surface broad questions people are actively seeking. The structured points and highlighted terms usually reflect the answers and subtopics that matter most to users. If I want to go deeper, I click “Show more,” which reveals additional angles and follow-up questions I might not have considered initially.
AI cited sources by Google AI Overview
Finding and answering these questions helps you do lightweight online audience research and create content that feels genuinely helpful. It also increases the chances of your blog post being referenced in AI-generated answers, since LLMs are designed to surface clear responses to specific questions.
3. Structure your content with headings and subheadings
In our 2026 SEO predictions, we highlighted that editorial quality is no longer just about good writing. It has become a machine-readability requirement. Content that is clearly structured is easier to understand, reuse, and surface across both search and AI-driven experiences.
How LLMs use headings
AI models rely on headings to identify topics, questions, and answers within a page. When your content is broken into clear sections, it becomes easier for them to extract key information and include it in AI-generated summaries.
Why headings still matter for SEO
Headings help search engines understand the hierarchy of your content and the main points you are trying to rank for. They also improve scannability and usability, especially on mobile devices, and increase the chances of earning featured snippets.
Good structure has always been a core SEO principle. In the AI era, it remains one of the simplest and most effective ways to improve visibility and discoverability.
4. Focus on readability aspects
An SEO-friendly blog post should be easy to read before it can rank or get picked up by AI systems. Readability helps readers stay engaged and helps search engines and AI models better understand your content.
A few key readability aspects to focus on while writing:
Avoid passive voice where possible Active sentences are clearer and more direct. They make it easier for readers to understand who is doing what, and they reduce ambiguity for AI systems processing your content.
Use transition words Transition words like “because,” “for example,” and “however” guide readers through your content. They improve flow and make it easier to follow relationships between sentences and paragraphs.
Keep sentences and paragraphs short Long, complex sentences reduce clarity. Breaking content into shorter sentences and paragraphs improves scannability and comprehension.
Avoid consecutive sentences starting in the same way Varying sentence structure keeps your writing engaging and prevents it from sounding repetitive or robotic.
The readability analysis in the Yoast SEO for WordPress metabox
If you are a WordPress or Shopify user, Yoast SEO (and Yoast SEO for Shopify for Shopify users) can help here. Its readability analysis checks for passive voice, transition words, sentence length, and other clarity signals while you write. If you prefer drafting in Google Docs, you can use the Yoast SEO Google Docs add-on to get the same readability feedback before publishing.
Use Yoast SEO in Google Docs
Optimize as you draft for SEO, inclusivity, and readability. The Yoast SEO Google Docs add-on lets you export content ready for WordPress, no reformatting required.
Good readability is not just about pleasing algorithms. It helps readers understand your message more quickly and makes your content easier to reuse in AI-generated responses.
5. Use inclusive language
Inclusive language helps ensure your content is respectful, clear, and welcoming to a broader audience. It avoids assumptions about gender, ability, age, or background, and focuses on people-first communication.
From an SEO and AI perspective, inclusive language also improves clarity. Content that avoids vague or biased terms is easier to interpret, digest, and trust. This directly supports brand perception, especially when your content is surfaced in AI-generated responses.
Yoast SEO supports this through its inclusive language check, which flags potentially non-inclusive terms and suggests better alternatives. This feature is available in Yoast SEO, Yoast SEO Premium, and in the Yoast SEO Google Docs add-on, making it easier to build inclusive habits directly into your writing workflow.
Inclusive language ensures your content is intentional, thoughtful, and clear, aligning closely with what modern SEO and AI systems value.
6. Add relevant media and interaction points
A well-written blog post should not feel like a long block of text. Adding the right media and interaction points helps guide readers through your content, keeps them engaged, and encourages them to take action.
Why media matters
Media elements such as images, videos, embeds, and infographics make your content easier to consume and more engaging. Blog posts that include images receive 94% more views than those without, simply because visuals break up large blocks of text and make pages easier to scan.
Video content plays an even bigger role. Embedded videos help explain complex ideas faster and can significantly improve organic visibility compared to text-only posts. Together, these elements encourage readers to stay longer on your page, which is a strong signal of content quality for search engines and AI systems alike.
Media also improves accessibility. Properly optimized images with descriptive alt text make content usable for screen readers, while original visuals, screenshots, or diagrams help reinforce credibility and expertise.
Use interaction points to guide and engage readers
Interaction does not always mean complex features. Even simple elements can significantly improve engagement when used well.
Table of contents and sidebar CTA used as interaction points in a Yoast blog post
A table of contents, for example, allows readers to jump directly to the section they care about most.
Other interaction points include clear calls to action (CTAs) that guide readers to the next step, relevant recommendations that encourage users to keep exploring your site, and social sharing buttons that make it easy to amplify your content. Interactive elements like polls, quizzes, or embedded tools further encourage participation and increase time on page.
7. Plan your content length
Content length still matters, but not in the way many people think it does.
A common question is what the ideal word count is for a blog post that performs well. A 2024 study by Backlinko found that while longer content tends to attract more backlinks, the average page ranking on Google’s first page contains around 1,500 words.
That said, this should not be treated as a fixed benchmark. The ideal length is the one that fully answers the user’s question. In an AI-driven era, publishing long content that adds little value or is padded with unnecessary fluff can do more harm than good.
If a topic genuinely requires a longer format, breaking the content into clear subheadings makes a big difference. I personally prefer structuring long articles this way because it improves readability, helps readers navigate the page more easily, and makes the content easier for search engines and AI systems to understand.
If you use Yoast SEO or Yoast SEO Premium, the paragraph and sentence length checks can help here. These checks exist to prevent pages from being too thin to provide real value. Pages with very low word counts often lack context and struggle to demonstrate relevance or expertise. Yoast SEO flags such cases as a warning, while clearly indicating that adding more words alone does not guarantee better rankings.
Think of word count as a guideline, not a goal. Your focus should always be on clarity, completeness, and usefulness.
8. Link to existing content
Internal linking is one of the most underrated SEO practices, yet it does a lot of heavy lifting behind the scenes.
By linking to relevant content within your site, you help readers discover additional resources and help search engines understand how your content is connected. Over time, this strengthens topical authority and signals that your site consistently covers a subject in depth.
Good internal linking follows a few simple principles:
Link only when it adds value and feels natural in context
Use clear, descriptive anchor text so users and search engines know what to expect
Avoid linking to outdated URLs or pages that redirect, as this wastes crawl signals
Internal links also keep readers engaged longer by guiding them to related articles. This improves overall site engagement while reinforcing your expertise on a topic.
From an AI and search perspective, internal linking plays an even bigger role. Modern search systems analyze content structure, metadata hierarchies, schema markup, and internal links to assess topical depth and clarity. Well-linked content clusters make it easier for search engines and AI systems to understand what your site is about and which pages are most important.
For WordPress users, Yoast SEO Premium offers internal linking suggestions directly in the editor. This makes it easier to spot relevant linking opportunities as you write, helping you build stronger content connections without interrupting your workflow.
A smarter analysis in Yoast SEO Premium
Yoast SEO Premium has a smart content analysis that helps you take your content to the next level!
Meta titles and meta descriptions help users decide whether to click on your content. While meta descriptions are not a direct ranking factor, they strongly influence click-through rates, making them an essential part of writing SEO-friendly blog posts.
A good meta title clearly communicates what the page is about. Place your main keyword near the beginning, keep it concise, and aim for roughly 55-60 characters so it doesn’t get truncated in search results.
Meta descriptions act like a short invitation. They should explain what the reader will gain from clicking and why it matters. Instead of stuffing keywords, focus on clarity and usefulness. Mention what aspects of the topic your content covers and how it helps the reader. Simple language works best.
Pro tip: Using action-oriented verbs such as “learn,” “discover,” or “read” can also encourage clicks and make your description more engaging.
If you use Yoast SEO Premium, this process becomes much easier. The AI-powered meta title and description generation feature helps you create relevant, well-structured metadata in just one click. It follows SEO best practices while producing descriptions and titles that are clear, engaging, and aligned with search intent.
Bonus tips
Once you have the fundamentals in place, a few extra refinements can go a long way. The following bonus tips help improve usability, clarity, and long-term discoverability. They are not mandatory, but when applied thoughtfully, they can make your blog posts more helpful for readers and easier to surface across search engines and AI-driven experiences.
1. Add a table of contents
A table of contents (TOC) helps readers quickly understand what your blog post covers and jump straight to the section they care about. This is especially useful for long-form content, where users often scan rather than scroll from top to bottom.
From an SEO perspective, a TOC improves structure and readability and can create jump links in search results, which may increase click-through rates. It reduces bounce rates by helping users find answers faster and improves accessibility by offering clear navigation.
By the way, did you know Yoast can help you here too? Yes, the Yoast SEO Internal linking blocks feature lets you add a TOC block to your blog post that automatically includes all the headings with just one click!
2. Add key takeaways
Key takeaways help readers quickly grasp the main points of your blog post without having to read the whole post. This is especially helpful for time-constrained users who want quick, actionable insights.
Summaries also support SEO by reinforcing topic relevance and improving content comprehension for search engines and AI systems. Well-written takeaways might increase visibility in featured snippets and “People also ask” results.
If you use Yoast SEO Premium, the Yoast AI Summarize feature can generate key takeaways for your content in just one click, making it easier to add concise summaries without extra effort.
3. Add an FAQ section
An FAQ section gives you space to answer specific questions your readers may still have after reading your post. This improves user experience by addressing concerns directly and building trust.
FAQs also help search engines better understand your content by clearly outlining common questions and answers related to your topic. While they can support rankings, their real value lies in reducing friction, improving clarity, and even supporting conversions by clearing doubts.
4. Short permalinks
A permalink is the permanent URL of your blog post. Short, descriptive permalinks are easier to read, easier to share, and more likely to be clicked.
Good permalinks clearly describe what the page is about, avoid unnecessary words, and include the main topic where relevant. They improve usability and help search engines understand page context at a glance.
5. Focus on building authority (EEAT aspect)
Building authority is critical, especially for sites that cover sensitive or high-impact topics. Demonstrating Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) helps both users and search engines trust your content.
This includes citing reliable sources, showing real-world experience, maintaining consistent quality, and clearly communicating who is behind the content. Strong E-E-A-T signals are especially important for YMYL topics, where accuracy and credibility matter most.
6. Plan content distribution
Writing a great blog post is only half the work. Distribution helps your content reach the right audience.
Sharing posts on social media, repurposing key insights into newsletters, and earning backlinks from relevant sites can drive more traffic and visibility. Distribution also increases engagement signals and helps your content gain traction faster, which supports long-term SEO performance.
Target your readers always!
In AI-driven search, retrieval beats ranking. Clarity, structure, and language alignment now decide if your content gets seen. – Carolyn Shelby
This perfectly sums up what writing SEO-friendly blog posts looks like today. Success is no longer just about rankings. It is about being clear, helpful, and easy to understand for both readers and AI systems.
Throughout this guide, we focused on the fundamentals that still matter: understanding search intent, structuring content well, improving readability, using inclusive language, and supporting your writing with media, internal links, and thoughtful metadata. These are not new tricks. They are strong SEO foundations, adapted for how search and discovery work in the AI era.
If there is one takeaway, it is this: always write for your readers first. When your content genuinely helps people, answers their questions, and respects how they search and read, it naturally becomes easier to surface across SERPs and AI-driven experiences.
Good SEO has not changed. It has simply become more human.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2026-02-10 14:16:342026-02-10 14:16:34Tips and tricks to write SEO-friendly blog posts in the AI era
Fun fact:
