Hi everyone!

This week Google added a new panel to Search Console that reports AI Overviews and AI Mode impressions. A welcome step. But that report alone won't carry you. It only sees Google's own AI surfaces, it gives you no click data, and it doesn't tell you how you show up for a given question. The real question is: do ChatGPT, Perplexity, and Gemini also recognize you, describe you correctly, or push your competitor forward instead?

I've said this for years: brand visibility in AI search is not a one-time snapshot, it's a trend that shifts week to week. Only the people who measure it consistently can see it. This week I'm turning that measurement into a system. In the headline I build, screen by screen, a Claude Cowork scheduled task that audits your brand across five engines (ChatGPT, Perplexity, gemini.google.com, Google AI Mode, and AI Overviews) every week, benchmarks you against competitors, checks whether you're being cited, and on top of all that computes the information gain of your content. This goes one step beyond the simple "prompt list" audits making the rounds; it's the version Stradiji built for itself.

Grab your coffee, let's dig in.

Brand visibility in AI search isn't a one-off audit, it's a trend you have to watch week to week. The "paste these 15 prompts into Google AI Mode" audits going around are a decent start, but they have three gaps: they look at a single engine, they're done by hand (and forgotten three weeks later), and they only ask "did I show up?" — never "how much original value did I add?" The version Stradiji built closes all three. We build a Claude Cowork scheduled task that runs your brand questions automatically every week across ChatGPT, Perplexity, gemini.google.com, Google AI Mode, and AI Overviews, benchmarks you against competitors, checks whether you're being cited (citation = the AI linking to your site in its source list), and on top of that scores your content's information gain (Chris Long's rubric, Google Patent US11354342B2). Instead of a hand-run audit, you get a self-running measurement system grounded in GEO principles.

I keep coming back to this: there are two distinct ways to appear in AI search, and you can't conflate them. A mention is when the AI names your brand as an option inside the answer. A citation is when the AI links to your site in its source list, using your content as evidence. They're not the same. A mention is brand awareness; a citation is real traffic. Most brands track neither right now.

The second issue is engine diversity. The Search Console report that launched this week only sees Google's AI surfaces. But your buyer asks ChatGPT, researches on Perplexity, consults Gemini. Each of these engines may know you differently; you can lead on one and be invisible on another. A brand that measures visibility through a single engine is missing half the picture.

The third is competition. Knowing your own impression count is half-knowledge. The real question is: who does the AI recommend for that same query? You, or your competitor? Which sources is your rival cited from while you're not? That's exactly where the audit earns its keep: putting your position side by side with your competitor's.

These three axes (mention/citation, multi-engine, competition) form the backbone of the audit. Now let's turn it into a task that runs on its own.

The task's input is a prompt list tailored to your brand. Fill the prompts below in with your own brand name, category, company size, and target audience. Paste them into a prompts.md file and drop it in a folder Cowork can reach. The set I use for Stradiji has four groups.

Visibility (does the AI know your brand?):

Brand search (do they describe you correctly?):

Citation check (do you show up as a source?):

Competitor benchmark (where do you sit in the consensus?):

That last prompt is the most diagnostic; it maps where you appear and where you go quiet across the whole buyer journey in a single answer. Save it for last.

Open a new chat in Claude Cowork and describe the task. The brief has to be precise, because the task runs while you're away. Here's the brief I use:

"Process every prompt in prompts.md in order. For each prompt, assess how my brand appears in AI search: am I mentioned, am I cited as a source, which competitors stand out, and which sources is the AI pulling from? Do this assessment separately for five engines: ChatGPT, Perplexity, gemini.google.com, Google AI Mode, and Google AI Overviews. Run the same prompts on each engine and compare the results."

The critical move here is naming the five engines explicitly. Cowork can reach these engines through the browser and run the searches; but if you don't say which ones you want, it'll guess. Spell out ChatGPT and Perplexity, Gemini (gemini.google.com), Google AI Mode, and the AI Overviews that appear in classic search, one by one, so the picture is complete.

A detail that multiplies the audit's value: if the AI isn't citing you, who is it citing, and why? Add this to the brief: "For each prompt, list the sources the AI references (sites, reports, YouTube videos, Reddit threads, review platforms). Note which of these sources carry my competitor's content but not mine."

This produces a direct roadmap for your content strategy. Say that for a certain question the AI is feeding off three YouTube videos and you have no video on that topic. That single observation answers "what content should I produce this week?" Reddit, YouTube, and review platforms (G2, Capterra and the like) are among the sources AI cites most often; have the task scan those specifically.

Just checking "did I show up, was I cited?" is half the job. The real question is: why should the AI cite you at all? Google makes that call on information gain — for the same query, how much new information does a page add that the others don't? Chris Long's Information Gain rubric (Google Patent US11354342B2) measures this across six dimensions: first-party evidence (invoices, screenshots, your own data), firsthand experience ("I did it, saw it, built it"), specificity (named people, exact numbers, real dates), point of view (content with a thesis), the LLM moat (could ChatGPT write this from training data alone?), and information gain (what are you teaching that isn't in the top three results?).

Add this to the brief: "For every question where my brand isn't cited, read the top three organic results, list the information those pages have that mine doesn't. Then score my relevant content on the six dimensions above and tell me which dimension I'm weak on." The output won't just say "I'm not showing up"; it'll say "that page has a real customer case, yours has generic advice, that's why it's cited and you're not." That's a diagnosis you can act on directly. This is the core of Stradiji's GEO approach: AI doesn't cite commodity content that anyone could write; it cites non-commodity content that only you could write.

Add the save rule to the brief: "Write the results to AI_Visibility_Audit/Report_YYYY-MM-DD.md. In the report, give each engine its own section, summarize mention/citation status in a table, and collect competitor benchmarks and content gaps under separate headings." The dated filename means a baseline accumulates every week; lay two weeks' reports side by side and you can see the trend.

To set the schedule, just type something like "run this task every Monday at 9 AM" into the chat. Cowork offers to save it as a scheduled task, and you confirm. From then on, five engines get scanned every Monday without you lifting a finger, and the report lands in your folder.

Start the first report by hand and read it carefully. Do the prompts recognize your brand correctly? Does the competitor list make sense? If one engine doesn't see you at all, that's a serious visibility gap in that ecosystem. Refine the prompts if needed and update prompts.md; the task runs with the new version next time.

One caveat: AI answers vary. The same prompt can show different sources on different days. So don't draw firm conclusions from a single report; gather at least three or four weeks of data and read the trend. The task collects the data; you make the call. The real work is reading that data and updating your content and PR strategy — that part is still a human job.

You can get stuck in three places when you actually build this. First, permissions. The task uses the browser; on the first run Cowork asks for permission for Chrome and other tools. The moment you create the task, trigger it once with "Run now" and approve the permissions up front. Otherwise Monday morning the task sits waiting on a permission screen and never runs. Second, don't write the source list from memory. Don't set the task up around "AI feeds off Reddit and YouTube" just because you read that somewhere; it varies by vertical. Have the task ask the engines directly each week, "which sources did you base this recommendation on," and let it bring back the real sources. Third, build the competitor list correctly. I didn't guess my competitors; I pulled stradiji.com's organic competitive set from Semrush (Zeo, Webtures, AnalyticaHouse, SEMpeak, Digipeak). Define your own competitors from data, not memory.

When I set this task up for Stradiji and ran the first audit, the result didn't surprise me, but it drew a clear picture. There are two separate worlds.

On brand and personal queries ("who is Stradiji," "who is Mert Erkal," "what's their reputation"), we show up, and the sentiment is positive — meaning the AI uses positive, trust-building language when it talks about us. It knows us from LinkedIn and the client testimonials on stradiji.com, and it finds that we're described as "the doctor for sites losing traffic to technical errors" on a major local tech forum. No problem there.

But on commercial queries like "best SEO agency / GEO agency in [my market]," we don't show up at all. The striking part is how the agencies that do show up got there. I looked myself: one agency put a different firm at #1 and itself at #2 in its own blog post titled "the best GEO agencies in [city]." The AI takes that list as a source and presents that agency as "among the best." So the AI is being flat-out gamed by self-promoting ranked lists (listicles — "top 10 agencies" style content). The same phrases repeat across dozens of sites; this is called recommendation poisoning — spreading the same message across the web to get the AI to present a particular brand as the top recommendation. And the AI mistakes that repetition for "consensus."

This is GEO's dirtiest spot right now. It looks like it works in the short term. But as Lily Ray has warned repeatedly in 2026, this kind of synthetic citation building and pile of self-promotional listicles is flagged as a spam signal by Google and Microsoft; it carries algorithmic-penalty risk in the long run. Stradiji won't play that game. Our path is what the AI actually values: original data, real case studies, firsthand experience, and digital PR with genuine news value. Not stuffing lists, but producing proof.

Instead of reading that report every week, I piped the task's results into a live dashboard. Every Monday the task both writes the dated report and refreshes this panel. The dashboard shows an overall visibility score, the status on each of the five engines, Stradiji and Mert Erkal tracked separately, sentiment and which source it comes from, a competitor benchmark, the weekly trend, and most importantly a matrix of the audited prompts. Prompts where Stradiji never appears get flagged automatically as "content gaps"; those become the priority list for non-commodity content. The panel is bilingual, English and Turkish, with one click to switch.

The dashboard isn't meant to replace our GeoGenie.ai panel. GeoGenie is the core measurement layer for our enterprise client campaigns; this Cowork dashboard is a lightweight, fast-to-build complementary layer where I can track my own brand and any prompt I want. The two work together.

For three years I've been saying "measure your AI visibility" in this newsletter. This week we turned that sentence into a system. Because measurement done once doesn't work; in this new era the winner isn't whoever produces the most content, it's whoever tracks visibility most consistently and adapts fastest. At Stradiji we run our GEO campaigns through GeoGenie.ai; these lightweight Cowork automations we build ourselves run right alongside it, and the two complement each other. This is the strongest lever in your hands too: set it up once, let it run every week, and you just read the report and act.

On June 7, 2026, Google published new guidance on third-party SEO tools, services, and advice. According to Search Engine Journal's Roger Montti, this is Google's "strongest assertion of authority yet" over SEO knowledge. Marie Haynes flagged the update on LinkedIn too.

The guidance carries four messages. Google positions its own documentation as the objective truth of SEO advice; it extends that same authority claim to AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) advice; it distances itself from third-party tools ("Google doesn't endorse any tool, they can't access our internal ranking data, they can't guarantee performance"); and it recommends its own tool ("use Search Console"). Plus a clear warning: "For an SEO audit, grant only read access to Search Console; if someone guarantees you first place, find someone else."

My read is layered. Building on Google's official documentation is always good practice. What's new here is the tone: splitting SEO knowledge into "us" versus "them" and declaring itself the only real source. For an agency that does GEO consulting, this is directly relevant. Our stance is clear: we never say "Google approved this," and no tool guarantees rankings. We use tools like GeoGenie for multi-engine visibility, and we don't claim they hold Google's internal data. Montti's question hangs in the air: why is Google doing this now? Is a new algorithm coming to target SEO that diverges from Google's own, or is it simply cementing its authority? You have to be ready for both.

There's a valuable observation from Eli Schwartz here. In his conversation on Ross Hudgens' Siege Media podcast, Schwartz sums up Google's new AI search guidance in one line: "This is basically just SEO." That is, the work behind new labels like AEO and GEO is fundamentally the SEO we've always done; manipulation isn't a strategy. Schwartz's second striking point, which Nick LeRoy also underscored on LinkedIn, is the gap between what companies expect from their SEO teams and what they actually get: the SEO career path is broken, but demand for real SEO has never been higher. I'm with him on this. Most titles like "AEO expert" and "GEO expert" are just an added layer for AI engines on top of solid SEO fundamentals. Schwartz's strongest suggestion: the best SEOs now think like product managers, they build things. The Cowork task automation I walked through in the headline is exactly that — SEO that builds a system, not SEO that requests a report.

Google announced the May 2026 Core Update finished rolling out on June 2; the rollout started May 21 and took about 12 days. Aleyda Solis analyzed SISTRIX data for the US and UK afterward. Her finding is clear: sites that best fit a query's intent, market, and result type gained; those a step removed from that fit lost.

Concrete examples. Some high-authority domains dropped (nytimes.com, nih.gov). Original sources gained: in the UK, cambridge.org rose 40.9% while the pronunciation tool youglish.com fell 69.6%. Local sites overtook global .coms: amazon.co.uk rose 21.3% while amazon.com fell 54.6% for UK users. Forums pulled back (reddit.com fell 23.8% in the UK), but larger social and video platforms stayed flat to positive.

This finding is critical for our global clients. Solis's emphasis is the rise of local domains; as a Turkey-based agency serving the US, UK, and Australia, that's directly our concern. International sites should be checked for "ranking in the wrong market" and "weak country signals." Practical action: for every important query, check which result type won after the update, and make sure your page is that type, not a weaker copy of a source that already owns the space.

Google announced this week that it's adding new Search Generative AI performance reports to Search Console. The report gives AI Overviews and AI Mode impressions, broken down by impression, page, country, device, and date. But it has three notable gaps: no click data, it only covers Google's AI surfaces (not ChatGPT, Perplexity, Gemini), and it's UK-first for now. Google also added a toggle that lets you remove your site from AI surfaces.

Let me stress this: it's the most important GSC update in three years, but it doesn't replace the audit task from the headline, it complements it. GSC tells you "how many impressions did you get"; the audit task tells you "on which question am I mentioned, on which am I cited, where do I stand across engines, what's my information gain score." Keep the toggle on without overthinking it; turning it off cuts your citation potential too. Until the report reaches more markets, build your baseline with your own task automation, so you enter the rollout with stronger data.

Google opened up a way to connect Google Business Profile directly to Google Analytics. Once you set up the link, local metrics (calls, directions requests) flow straight into your Analytics reports; there are seven metrics: interactions, website clicks, calls, directions, messages, bookings, and menus. You set up the connection under "Product links" in the Admin panel. The limit: connect more than one profile and the metrics get merged with no per-location breakdown; data is retained for six months.

I'd add this: it's a real win for single-location local businesses. Until now Analytics could only see Business Profile traffic through UTM tags; this direct connection brings calls, directions, and bookings next to your web data. Multi-location brands benefit less. For clients running local SEO, my recommendation: set up the connection, but don't drop the Business Profile dashboard and the Performance API for detailed analysis.

Cloudflare CEO Matthew Prince said automated traffic now makes up 57.3% of HTTP requests to HTML content; humans are at 42.7%. Prince predicted at SXSW in March that bots would overtake humans by 2027; the line has already been crossed. His point matters: AI agents generate far more web activity than humans because they gather information differently. A human visits five sites; an agent visits thousands.

This data tells me one thing: the agentic web is today's reality. Your content being machine-readable, authoritative, and interpretable by AI systems is no longer optional. Schema markup, clean HTML, a clear heading hierarchy, and llms.txt aren't just for SEO; they're for the bots that now make up the majority of your visitors.

Google started rolling out Search profiles within Google Discover for US publishers. Search profiles give publishers a followable landing page: a header image, a follow button, and the latest articles, videos, and social posts in one place. Claiming a profile can create a Knowledge Panel for eligible creators.

I think this is worth watching for E-E-A-T signals. As someone working to grow a YouTube channel, I'm tracking it personally too; a profile strengthens being recognized as an entity. No launch date for outside the US yet, US-first. If you have a Knowledge Panel, keep your avatar and social links current.

Manus released a Shopify integration: you can build and grow a Shopify store from a single chat. There are three functions. Build: brand identity, navigation, product pages, and a cart wired to Shopify checkout, from one command. Manage: drop an Excel and product photos into the chat, and Manus writes the listings and matches images to SKUs. Grow: ask which products are selling slowly, and Manus turns the answer into ad creative and campaign ideas. Per the announcement, Manus is now part of Meta.

To me this is a concrete example of agentic commerce (AI agents running commerce). For e-commerce clients, think about it two ways: on one hand these tools speed up operations; on the other, your product data (structured data, clear product descriptions) being readable by AI agents turns into a competitive edge. If an agent builds the store for you, remember it lists competitor products just as easily; the difference opens up in the quality of your brand and product data.

Brand visibility in AI search isn't a one-time audit but a trend to watch week to week; this week we turned that audit into a Claude Cowork task that runs automatically every week across ChatGPT, Perplexity, Gemini, AI Mode, and AI Overviews — and that's exactly where the real leverage is.

None of these moves work in isolation. Building the audit task, reading the new Google guidance, rebuilding pages weakened by the core update — they fit together when you work through them in sequence. If you'd like to keep up with these moves in real time, SEOs Diners Club is where I share the weekly read; if you want to go deeper with strategy on specific markets or verticals, that's what Stradiji does for enterprise clients in the US, UK, and Australia.

If this newsletter has been useful to you, you can add Stradiji.com as a Preferred Source in Google with this link. One click, five seconds, and we'll meet more often inside Google's AI answers.

See you next week with more.

Mert Erkal Stradiji

I genuinely enjoy sharing what's moving in SEO and AI search with you every week. If you find the work useful, you can keep it going by buying me a coffee. ☕ Click 'Buy Me a Coffee' to contribute to the knowledge-sharing. Let's build more together.

Mert Erkal is a digital marketing and SEO expert with 15+ years of experience. As the founder of Stradiji, he provides consulting on SEO strategy, GEO (Generative Engine Optimization), conversion rate optimization, and AI integration to global brands across the US, UK, Australia, and beyond.

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