I’m excited to share with you my journey into optimizing websites for AI agents. Let’s dive into what Agentic AI SEO is all about and how we can make our sites more appealing to these intelligent algorithms.
Imagine transforming your website from just another set of blue links on a search result page to a dynamic, task-oriented AI experience. This is where AI agents come in, and I’m here to guide you through optimizing your site with structured data and machine-readable context.
By leveraging structured data, we ensure that AI agents understand and interact with our content seamlessly. It’s crucial to use safe actions and APIs to optimize our site’s functionality and accessibility, enhancing user experience and ultimately, achieving better search visibility.
Join me in this complete guide to implementing Agentic AI SEO strategies, and let’s revolutionize our websites together for the era of AI.
I often wonder where artificial intelligence gathers its vast data from. It’s a fascinating journey from web crawls to precisely licensed datasets.
If you’re like me, you’re eager to see your content become a trusted, reputable source in AI’s intricate network of answers. This process significantly benefits from AEO best practices.
What’s more exciting is becoming part of this AI data revolution by understanding how AI leverages data and how we can strategically position our content to be at the forefront.
Last week, I was eager to see if Google would incorporate Gemini 3 into their AI systems. Now, it’s official: some responses in AI Mode are powered by Gemini 3, but it’s only available to Google AI Pro & Ultra subscribers in the U.S.
Nick Fox, Google’s SVP of Knowledge and Information, mentioned on X that the rollout of Gemini 3 in search is ongoing. He highlighted that they’ve implemented intelligent automatic model routing to Gemini 3 Pro, aimed at tackling the most challenging questions in AI Mode.
Previously, Fox included AI Overviews in this rollout. However, his latest updates have corrected this to focus solely on AI Mode. If you are a subscriber, you’ll know this feature is available if it’s an option within the AI Mode tab’s carrot menu.
From a recent blog post by Google’s Head of Search, Liz Reid, there’s an emphasis on enhancing automatic model selection in Search with Gemini 3 over the coming weeks. This means your complex queries in AI Mode could soon be channeled to this advanced model.
Introduced on November 18, 2025, Sundar Pichai, Google’s CEO, described Gemini 3 as their most intelligent model yet. It combines all of Gemini’s capabilities, aiming to bring any idea to life.
I’m particularly excited because some users might notice more visual and comprehensive results in AI Mode, especially if you’re an AI Pro or Ultra subscriber in the U.S. These changes indicate that Gemini 3 is already reshaping the search landscape.
Eventually, all AI responses will be powered by Gemini 3 until the next update is rolled out by Google. I can’t wait to see how this further enhances search experiences.
I’m excited to share insights from the rigorous testing of Google Ads’ new AI tool, Nano Banana Pro. This innovative tool is creating quite a buzz with its ability to swiftly generate seasonal, mood, and lighting variations for visual assets, making it perfect for brainstorming and quick asset production.
Incorporating conversational image generation and editing, Nano Banana Pro easily integrates directly into campaigns. This tool empowers advertisers to create visuals that are seasonally, mood-oriented, and material-specific without needing an extensive photoshoot. This functionality aligns with Google’s larger strategy, alongside its AI writing tool, Opal, to speed up content creation across Performance Max, Display, and other automated campaigns.
Driving the news. This extensive testing was spearheaded by Ameet Khabra, founder of Hop Skip Media, who evaluated the tool’s performance across industries such as mattresses, HVAC, and real estate. Her findings reveal that while Nano Banana Pro delivers impressive visuals in certain aspects, advertisers should be aware of its limitations before relying on it exclusively.
The good:
Accurate seasonal transformations and lighting adjustments.
Material and finish edits, especially for items like kitchen cabinets and furniture, maintain texture and perspective.
Reliable guidance for adding larger objects and achieving correct placement in general marketing contexts.
Able to refine prompts, offering richer instructions.
The bad:
Brand constraints limit the use of logos, branded products, and detailed text overlays.
Persisting issues with demographic bias and object placement errors.
Combining unrelated images or zooming out can sometimes result in unrealistic outputs.
The weird:
Mixing seasons or literal misinterpretations of prompts like “luxury” or “masculine” can occur.
Strong holiday-themed additions may overshadow subtle messaging.
Bottom line for advertisers. Ameet Khabra suggests that Nano Banana Pro is most effective for ideation, seasonal changes, or asset-heavy campaigns such as Performance Max or Display. It’s not yet ready to replace professional creatives in high-stakes or brand-sensitive campaigns. Advertisers should continue to conduct tests in isolated asset groups and rely on human reviews.
Why advertisers should care. Quickening the pace of creative production can alleviate campaign bottlenecks and boost testing volumes—but caution is necessary to avoid off-brand visuals, poor click-through rates, and misaligned automation signals. When used judiciously, Nano Banana Pro can be a valuable tool for creativity; if used indiscriminately, it might lead to subpar imagery.
I’ve just learned that Google Ads has introduced an exciting update that now allows us to create up to five custom views on the Overview tab. This change makes it so much simpler for us to track the key metrics that are crucial for our advertising campaigns.
Google Ads is really stepping up its game by letting us customize the Overview tab. Now, we’re not limited to a single static view. Instead, we have the power to tailor our dashboards, ensuring that we focus on the data that truly impacts our campaigns.
Driving the news. I’ve seen a post on LinkedIn, complete with screenshots, that highlights this new update. Users can now add multiple tabs and fully personalize their Overview pages, fitting their unique needs.
What’s changing. In the past, the Overview tab had a fixed layout. This was restrictive for us, especially when we wanted more detail on our performance. Now, with these custom views, we can organize metrics, charts, and reports in a way that really fits our workflow, allowing for better efficiency and insights.
Why we care. For those of us managing Google Ads, the ability to custom-tailor the Overview tab means we can focus directly on the metrics that matter, saving time and cutting down on the hassle of digging through various reports. For agencies handling multiple clients, this allows us to create personalized dashboards for each account, enhancing our efficiency and insight. Over time, this adjustment helps us spot performance trends more quickly and make data-driven decisions with greater confidence.
First seen. This new feature was first unveiled by Adrian Dekker.
Bottom line. This update makes account monitoring much more streamlined, enabling us to focus on the key performance indicators without having to filter through numerous reports. With custom views, organizing campaigns and spotting trends becomes a breeze.
I recently heard about Google’s discreet update on December 12th to its Personalized Ads policy. This change seems to be expanding access to Custom Segments for certain Display campaigns, opening up possibilities previously restricted under the policy.
The information dropped into my inbox through a mandatory service email from Google. However, it left much to the imagination as it only confirmed the policy update but failed to provide specifics. It made it clear, though, that the change targets campaigns limited by the Personalized Ads policy, not every Display campaign.
As someone who closely follows these updates, I noticed the buzz among industry experts. Google Ads Coach Jyll Saskin Gales pointed out that Custom Segments have mostly been available for Display campaigns, suggesting that this update focuses on previously blocked advertisers gaining access.
PPC Freelancer Sofia Akritidou raised critical questions, voicing the confusion many of us felt:
Could this mean a breakthrough for health-related advertisers who faced audience targeting blocks?
What about user comfort with ads tailored to sensitive conditions?
Does “Display campaigns” mean all GDN formats, possibly including Demand Gen?
Why hasn’t Google clarified these changes?
These are not just speculative queries—they are vital considerations for adjusting our strategies and campaigns. Google’s move could mean a broader reach with Custom Segments, allowing us to potentially engage with niche markets, including sensitive areas like healthcare. But it does raise the issue of user privacy.
I’m keen to know whether this change extends to Demand Gen campaigns. Clarity there could significantly influence strategic decisions as December 12th approaches.
What could this mean for advertisers like me? Well, here are a few possibilities:
Access to new targeting options for campaigns previously restricted by limited audience tools.
The advantage of crafting segments based on intent or interest, even with stringent policy guidelines.
The change was initially noticed by Chris Ridley, the Head of Paid, who shared the news on LinkedIn.
The bottom line here is clear: if your Display campaign falls under the Personalized Ads policy, you’re in for an upgrade in targeting capabilities. For others, it’s business as usual—for now.
I’ve discovered that mastering the Google Ads search terms report can revolutionize my targeting strategies, help cut unnecessary costs, and uncover exactly what potential customers are searching for.
You might believe you’ve got the hang of the Google Ads search terms report, but this crucial tool is often overlooked or misapplied. Let me share five personalized tips that can enhance the effectiveness of your campaigns, by using the search terms report effectively.
Keywords vs. Search Terms: A quick refresh
When I speak about keywords and search terms, the distinction can get blurry. Here’s a clear breakdown:
Keyword: It’s the word or phrase I add to my Search campaign to indicate the types of searches I want my ads to appear beside.
Search term: This is the actual phrase a user typed into Google that triggered my ad.
My ads appear for a search query and create a search term in my account due to:
Manually entered keywords.
Keywordless targeting using tools like Shopping Ads, Dynamic Search Ads (DSA), AI Max, or Performance Max.
Which campaign types have a search terms report?
The search terms report isn’t exclusive to Search campaigns; it’s available across various campaign types utilizing search queries:
Search Campaigns (can be keyword-based or keywordless via AI Max)
Shopping Campaigns (keywordless)
Performance Max (keywordless)
All these campaign types enable me to add negative keywords, helping fine-tune the targeting either through keyword lists or specific ad group levels. Regardless of the type, the search terms report remains my primary tool for understanding user intent and how ads align with real searches.
Tip 1: Your search terms have match types, too
Interestingly, every search term also has a match type, distinct from keyword match types. Here’s how I think about it:
A keyword match type is the rule I set for Google.
A search term match type reflects Google’s judgment on the alignment of a user query with that rule.
For instance, even if I set a broad match, the triggering search term may be seen as an “exact match close variant.” By exporting the search terms report into a pivot table by match type, I get a clear performance view, aiding in my optimization decisions.
Tip 2: The search terms report isn’t just for adding negatives
A common misstep I see is adding too many negative keywords from the search terms report. It’s important to add irrelevant queries as negatives, but needing to negate over 10% signifies deeper issues. Before jumping into adding negatives, I reassess my targeting strategy:
Are my keywords too broad?
Should I consider a narrower match type?
Is it time to turn off AI Max?
Do I need to refine my product feed for better matches?
By refining targeting from the outset, the amount of irrelevant traffic—and consequently the need to add negatives—diminishes. It’s crucial to be precise with how I match negative keywords to avoid conflicts.
Tip 3: Customize your search terms report for DSA or AI Max
If I rely on keywordless features like DSA or AI Max, I tweak my report view for comprehensive insights. By selecting the right dropdown options:
DSA View: Reveals landing pages for each search term, highlighting DSA’s query-page connection.
AI Max View: Displays landing pages and RSA headlines, helping evaluate the effectiveness of features like URL expansion.
Tip 4: Don’t ignore the “Other Search Terms”
I always pay attention to the “Total: Other search terms” row at the search term report’s bottom. Though these queries are hidden, likely for privacy or low volume, their performance data are insightful. Comparing visible vs. non-visible search term performance guides my targeting adjustments.
If “other search terms” excel, broadening targeting or employing more broad match keywords or AI Max might be beneficial.
If they perform poorly, narrowing targeting or using exact match keywords or a stricter strategy like Target CPA could be advantageous.
Tip 5: Analyze your search terms alongside their respective keywords
This simple yet impactful practice involves adding a Keyword column to see the keyword responsible for triggering each search term. If certain keywords frequently lead to irrelevant terms, I consider pausing or replacing them, while elevating effective search terms into distinct keywords.
Get more from your Google Ads campaigns
The search terms report is my gateway into understanding user behavior and preferences. These tips extend beyond mere negative keyword adjustments, empowering me to make precise decisions for optimizing Google Ads campaigns.
This article is part of the Search Engine Land series, “Everything you need to know about Google Ads in less than 3 minutes.” Each edition by Jyll provides insights into Google Ads features for optimal results, all designed for a quick 3-minute read.
As I explore the evolving landscape of search, I’ve discovered that dominating the top spot on the search results page is no longer the achievement it once was. By 2026, search will be more complex, with AI and multi-surface discovery shaping the future of organic success.
In this dynamic world, SEO professionals like me are asking critical questions. We need to ensure our strategies cover more than just traditional rankings. Are we reaching visitors who genuinely engage with us? Are we part of the AI and SERP experience? Are we anticipating trends early?
Jim Yu, CEO of BrightEdge, highlighted that search success used to mean climbing the ranks. Now, we see an expanded field with quick answers and AI layering. This prompts us to redefine our measures of success.
Here are the seven success criteria I believe will define organic search success in 2026:
1. Visitor Quality
We must ask ourselves: Are we attracting visitors who take worthwhile actions? Whether it’s demos for B2B or purchases for ecommerce, attracting qualified visitors is key.
How to Measure: Track conversion rates and revenue per session by segmenting organic traffic.
2. SERP Diversification
Beyond just aiming for a blue link, my goal now is to ensure visibility across various SERP features, including AI Overviews and People Also Ask sections.
3. Trendspotting
Recognizing and reacting to emerging topics before competitors can provide a crucial edge. I focus on identifying new and low-volume search trends that show potential.
4. Traffic Diversification
In a world where search means much more than Google, my strategy involves ensuring a presence across multiple platforms, including social media and marketplaces.
5. Brand Reputation
My aim is to cultivate trust and recognition wherever people encounter my brand. Consistent, positive visibility across all channels is crucial.
6. Ads and Media Support
Aligning SEO with paid media not only enhances ad performance but also ensures the content is optimized across all landing page experiences.
7. Combined Search Performance
Ultimately, my measures of success involve how search as a whole contributes to profitable growth. By integrating SEO with other channels, I can demonstrate a significant business impact.
In today’s digital world, the rise of AI-driven search and advanced conversational models like ChatGPT is transforming how we optimize content. It’s no longer just about traditional SEO tactics aiming for search engine rankings. Now, optimizing for AI answers ensures that our content reaches audiences through large language models (LLMs) more effectively. Let me guide you on tailoring content that works in harmony with AI systems like ChatGPT, while offering genuine value to readers.
AI models such as ChatGPT utilize natural language processing (NLP) to interpret and provide answers. They favor well-structured, clear content that directly addresses user queries. To craft content that these systems will rank and understand easily, I focus on how LLMs process and organize information. Here’s what I keep in mind:
Clarity and Specificity: I make sure to use straightforward, simple language to answer questions, steering clear of jargon unless absolutely necessary and industry-specific.
Contextual Relevance: I provide context to enrich my content and help AI draw connections and understand the scope fully.
Structured Data: Using headings, bullet points, and numbered lists ensures my content is easy to scan and digest.
For instance, when discussing “best hiking trails,” I’m sure to add specifics like trail names, their locations, difficulty levels, and unique features. This level of detail helps AI models pull precise answers.
I noticed that AI models get queried in a question-like format, such as “How do I optimize content for AI?” So, to optimize my content’s visibility in AI responses, I structure around common questions. I find tools like AnswerThePublic or Google’s “People Also Ask” helpful for identifying relevant queries.
Incorporate FAQs: By dedicating sections to frequently asked questions, I make the content more valuable.
Answer Directly: Beginning each section with a clear, direct answer followed by supporting details maintains interest and clarity.
Use Natural Language: Writing conversationally makes the interaction more genuine, as AI tends to mimic conversational patterns.
A section titled “What is AI content optimization?” would start with a brief definition and then roll into actionable advice.
Focusing on semantic search is essential because AI models function based on understanding context and intent. They no longer rely solely on exact keyword matches. Thus, I:
Use Related Terms: Including synonyms and phrases like “SEO,” “AI answers,” and “ChatGPT visibility” bolster the content’s reach.
Focus on Intent: I target the underlying goals of users. Someone asking about AI optimization likely wants actionable insights, not just theoretical knowledge.
Leverage LSI Keywords: Using Latent Semantic Indexing (LSI) keywords broadens my content’s relevance. Tools like LSIGraph provide useful terms.
AI models prioritize authoritative, up-to-date sources. Here’s how I ensure credibility:
Cite Reliable Sources: I back claims with studies, statistics, and expert opinions for added trust.
Update Regularly: Staying current by refreshing content keeps it in line with AI’s preference for recent information.
Show Expertise: Highlighting my credentials and experience helps to build confidence and authority.
Discussing AI optimization becomes more credible with recent NLP advances or industry leader quotes.
For AI systems, extracting information from structured content is key. So, I deploy these formatting techniques:
Short Paragraphs: Keeping paragraphs under 100 words aids in easy scanning.
Bullet Points and Lists: Summarizing key points in bullet lists is perfect for quick extraction.
Tables and Charts: Presenting data in tables, such as comparing various optimization methods, clarifies information.
While tailoring for AI, retaining user engagement is crucial too. Overstuffed content with keywords harms readability and engagement. I aim for a balance between AI-friendly and human-friendly text.
Testing content performance with AI tools like ChatGPT provides insights. I refine content based on whether it’s being cited, enhancing structure and specifics if needed. Monitoring analytics reveals how AI-driven traffic affects my site and informs ongoing optimization.
By crafting content with clear answers, semantic relevance, and reader-friendly formatting, I ensure my efforts align with ChatGPT and other AI models. It’s all about making my voice resonate in the era of conversational AI.
Inspired by this post on AnswerEngineOptimization.blog.
