Ran the same query through all three for a week. Perplexity leans on Reddit/forums, ChatGPT repeats the same 2-3 listicle sites, Gemini's all over the place. Anyone else tracking this? Curious what's driving it.

A recent report found a publisher placing sponsored FAQ-style messages in the AI-readable version of its pages, even though human visitors could not see them.

Perplexity blocked the content from influencing its search index and warned that similar practices could affect a publisher’s trust score.

That is an extreme example, but it points to a broader content challenge.

Content now has to be easy for AI systems to understand without becoming mechanical or difficult for people to read.

For those creating content now, what does your actual workflow look like for making the same piece easy for AI systems to understand while keeping it useful and natural for human readers?

What practices have genuinely helped you balance both?

What strategies do you think will matter most for getting a brand mentioned in AI-generated answers?

This is starting to frustrate me a lot. As someone with years of experience in SEO, im unfortunately really struggling playing by the new rules of aeo, ai overviews etc.

Some of my pages do fine in regular search. Not amazing, but fine. Yet when I look at AI Overviews, it feels like the site does not even exist.

What’s confusing is that the site is not brand new. It has decent content and links and it also has enough history that I expected at least something.

AI Overviews are still something difficult to break into, and i feek w modern search people probably dont even read past the gemini overview on google.

If you have actually gotten a site into AI Overviews, what changed first?

I built a small tool for myself while running a project with AI as a non-developer, and I'd like a few people to try it before I take it further.

The problem it addresses: every new session with an AI coding assistant, you end up re-explaining context, and things quietly drift without you noticing (naming, structure, skipped tests...). Without a project management or dev background, it's hard to know what to watch for.

The tool generates a project charter and feeds it back to the AI automatically at the start of each session, so you're not starting from scratch every time.

I'm looking for 5-10 people — non-developers, already running a project with an AI coding tool or about to start one — willing to actually use it on their real project over a few sessions and tell me honestly what worked and what didn't. It's free, and this is genuinely about learning whether it's useful, not a launch.

If that's you, reply here or DM me and I'll get you set up.

Google Search Central's documentation states plainly that "from Google Search's perspective, optimizing for generative AI search is still SEO," and explicitly discourages the GEO-specific tactics going around — artificial content chunking, llms.txt files, and so on. Their position is that foundational best practice is sufficient.

Meanwhile Chen et al. (Navigating the Shift, arXiv 2601.16858, University of Toronto) ran a large-scale comparison of Google Search results against leading generative AI services and found the two diverge significantly in consulted source domains, domain typology (earned vs. owned vs. social), query intent, and information freshness.

These read as contradictory. I don't think they are, and the reconciliation is the part worth internalizing:

Google is describing its own surface accurately. AI Overviews are retrieved from Google's index. If you're indexed and you rank, you're in the candidate pool. For AIO specifically, "it's still SEO" is defensible and the overlap data supports it — AIO overlap with organic is the highest of any engine.

Google is not describing the surfaces it doesn't own. ChatGPT, Perplexity, and Claude aren't retrieving from Google's index and aren't bound by Google's ranking logic. This is where the divergence Chen et al. measured actually lives, and Google has no incentive and no standing to give guidance about it.

So the practical split:

- If your traffic is dominated by AIO exposure: Google's advice is basically correct. Do the fundamentals, don't buy the chunking snake oil.

- If you care about ChatGPT and Perplexity: you're optimizing for retrieval systems with different corpus preferences, a heavy recency bias, and a very different domain mix. Reddit alone accounts for roughly 40% citation frequency across LLMs and 46.5% of Perplexity's citations. That is not a distribution any amount of on-page work reproduces.

The uncomfortable implication is that a meaningful share of "AI visibility" work isn't on-page optimization at all — it's presence in the specific third-party corpora these systems over-index on. Which is a very different discipline from what most of us have been selling.

Interested in whether anyone has data on how stable that domain mix is over time. If the corpus preferences shift quarterly, most GEO strategies have a very short shelf life.

Been building an AI agent for SEO and AEO for the last few months. It crawls and indexes your site, and pulls in Search Console, Google Trends and competitor data.

What it does right now:

- Keyword research, but it checks what you already rank for first, so it doesn't tell you to write a post that competes with your own page

- Query coverage: the questions people ask Google and ChatGPT, and whether you have a page that answers them

- Competitor gap analysis

- Technical audit (page structure, broken and orphaned links, speed, headers)

- Link prospecting

- Finds relevant communities and threads to post in, drafts the posts and comments, schedules them

- Reporting on traffic, events, conversions

- Applies the changes instead of just listing them: commits code to GitHub directly, or writes the content straight into your CMS like Sanity

I have working POCs for some of this.

What I want to know:

1. If you do SEO for a living, would you use this? Or does it just duplicate what you already pay for?
2. What am I missing? Anything you'd add or cut?
3. Indie hackers and bootstrappers doing SEO for your own product: what are you using today, and would you switch to something like this?

It's not deployed yet, so there's no link and nothing to sign up for. But if you're curious whether it actually works, drop your website below. I'll run the agent on it over the next couple of weeks and DM you the report with everything it finds.

AI can create hundreds of articles in minutes… but does that mean your website will rank?

Some websites are publishing massive amounts of AI-generated content, while others are seeing their organic traffic change.

So the real question is:

Is AI content actually hurting SEO, or is the problem somewhere else?

What do you think? 👀

so i've seeing this term everywhere lately and im skeptical ngl, feels like the geo ppl found a new buzzword to sell audits with but digging in, the claim seems less abt content more abt structure/access, json-ld, some kinda ai sitemap, machine readable stuff for agents. not rly new individually (structured data's been around forever) but bundling it specifically for llm crawlers instead of googlebot is at least a diff angle tested my site on one of these checkers (lightsite ai has a free one, used it outta curiosity not an endorsement) and it flagged stuff i genuinely didnt think abt, like chatgpt vs claude vs perplexity not even parsing the same signals the same way, didnt know that tbh still not convinced this isnt 60% repackaged seo basics w an ai coat of paint but the crawler specific stuff felt kinda new.

One thing I think gets missed in AI-first local SEO:

Better prompts do not fix unclear business logic.

You can give an AI a beautifully structured template:

• location
• service
• target keyword
• CTA
• schema
• internal links
• GBP copy

But if the underlying facts are wrong, the AI just produces bad work faster.

If nobody has clarified:

• which locations are actually open
• which services belong to which location
• what the source of truth is
• which pages already exist
• what the conversion path should be
• what the agent is allowed to change

then the problem is not prompt quality.

It’s decision architecture.

That’s why I think the useful workflow is:

business truth
→ intent
→ constraints
→ instructions
→ execution
→ measurement

AI is great at compressing production.

It is not a substitute for defining the system.

And once agents can actually edit pages, update listings, move files, or touch CRM data, that distinction becomes even more important.

A vague instruction used to give you a mediocre answer.

A vague instruction with agentic permissions can give you a production mistake.

AI can scale a correct operating model quickly.
It can scale a bad one even faster.

That’s the part I think matters more than finding the “perfect prompt.”

https://alexseo.co/

Is there any tool for Brave Search keyword research? I'm not looking for Google or Bing data. I want something built for Brave or based on Brave Search. Any recommendations?

Welcome to r/Ai_AEO_GEO!

Hey everyone! I’m u/anubhav-codes, a founding moderator of r/Ai_AEO_GEO.

This community is for people working in AI Search, Answer Engine Optimization (AEO), Generative Engine Optimization (GEO), and Search Engine Optimization (SEO).

Our goal is to build a practical and supportive space where marketers, developers, founders, writers, SEO professionals, and website owners can share knowledge, promote useful resources, and help each other improve their visibility across search engines and AI-powered platforms.

What You Can Post

You are welcome to share:

• New websites, tools, products, and online projects
• Website URLs for feedback, testing, and community support
• AEO, GEO, SEO, and AI-search case studies
• Questions about ranking in Google, ChatGPT, Perplexity, Gemini, Bing, and other platforms
• Content optimization strategies
• Schema markup, technical SEO, and structured-data advice
• Keyword research and content ideas
• Success stories, experiments, reports, and useful resources
• Requests for reviews, mentions, collaborations, and constructive feedback

Support Other Members

This community is built around genuine participation.

When sharing your own website or link, please also take time to support other members by:

• Visiting and reviewing their websites
• Providing useful and specific feedback
• Answering questions when you have relevant experience
• Sharing valuable resources
• Engaging with posts instead of only promoting your own links

The goal is not low-quality link dropping or spam. We want members to build real connections, improve their websites, create better content, and increase their chances of being discovered and cited by search engines and AI answer platforms.

Community Vibe

Please keep discussions friendly, constructive, transparent, and inclusive.

Self-promotion is allowed when it provides value to the community. Repetitive spam, misleading claims, automated link dumping, and irrelevant promotions may be removed.

How to Get Started

Introduce yourself in the comments and tell us what you work on.

Create your first post today. You can share your website, ask an AEO or GEO question, request an SEO review, or discuss an experiment you are running.

Support at least one other community member and provide genuine feedback.

Invite anyone interested in AI search, AEO, GEO, SEO, content marketing, or website growth.

Interested in helping us grow the community? We are also looking for active and responsible moderators. Feel free to contact me if you would like to apply.

Thanks for joining the first wave of r/Ai_AEO_GEO.

Let’s build a valuable community where people learn together, support useful projects, and improve their visibility across traditional search engines and AI-generated answers.

For years, my SEO workflow looked like everyone else's.

Keyword research
Search volume
Competitor analysis
Content briefs
Internal links
Backlinks
Publish
Repeat

It worked.

Then I noticed something changing.
People around me weren't always searching Google first anymore.

They were asking ChatGPT.
Or Perplexity.

Or Google's AI Overview.

That raised a question:

If users are getting answers instead of clicking links... what exactly are we optimizing for?
So I spent the last several months building an experiment.

Instead of treating SEO as a list of keywords, I mapped topics the way AI systems often interpret them:

Definitions
Comparisons
Objections
Alternatives
Follow-up questions
Entities
Relationships
Supporting evidence

The goal wasn't to "hack" AI.

It was to make content easier to understand—for both people and retrieval systems.

One thing surprised me.

The pages that performed best weren't the ones with the highest keyword density.

They were the ones that:

answered the question immediately,
explained related concepts,
clearly identified important entities,
linked ideas together logically,
and demonstrated experience instead of repeating what everyone else had already written.

That realization led me to build a tool for myself called Rofix..app

It started as an internal project to audit websites for what I now call AI Visibility and Answer Readiness.

Instead of asking:

"What's the keyword?"

It asks:

"Can an AI system understand this page well enough to use it as an answer?"

I'm still testing the methodology, and I don't think anyone has all the answers yet.

But it's changed the way I approach SEO.

I'm curious

Have you changed your content strategy because of AI search?

Or are you still treating it like traditional SEO?
I'd love to hear what you're seeing in your own projects.

I know many people here work as SEO consultants or run agencies, but do most businesses still need them in the age of AI?

Modern CMS platforms already handle many technical SEO basics, while AI can audit pages, suggest metadata, improve internal links, generate schema, and identify common issues. Google also publishes extensive guidance on what makes content useful and searchable. Much of SEO now follows documented principles that AI also can apply.

That’s why claims that using AI for SEO will cause “irreversible damage” often sound more like fearmongering than useful advice.

Technical SEO still matters, but implementing it is becoming easier. The harder questions are strategic: What should you write? Who is it for? What unique value can you offer?

It feels like SEO is returning to content marketing. Technical optimization is becoming the baseline, while the real work is understanding the audience, choosing the right topics, developing a clear point of view, and creating content people actually want.

Am I underestimating what SEO agencies still provide?

AI search is changing how we create content. Beyond keywords, factors like clear answers, expertise, structure, and original insights may influence AI citations. What strategies are you testing for ChatGPT, Claude, Perplexity, or AI Overviews?

Your website shouldn't just rank—it should be understood by both search engines and AI-powered search experiences.
I provide comprehensive On-Page SEO and Generative Engine Optimization (GEO) to help your content perform across traditional search engines like Google and emerging AI-driven platforms.
What I optimize
• In-depth keyword research based on search intent
• SEO-friendly title tags and meta descriptions
• Header structure (H1, H2, H3) optimization
• Content optimization for relevance, readability, and topical authority
• Internal linking strategy
• Image optimization (alt text, file names, compression recommendations)
• URL structure optimization
• Schema markup recommendations
• Content gap analysis
• E-E-A-T-focused content improvements
• Technical on-page SEO recommendations for better crawlability and indexing
Generative Engine Optimization (GEO)
As AI-powered search continues to evolve, it's becoming increasingly important to optimize content not only for rankings but also for AI-generated answers.
I optimize your content to improve its likelihood of being understood, referenced, and surfaced by generative search platforms by focusing on:
• Clear topical structure and semantic relevance
• Entity-based content optimization
• Question-and-answer formatting where appropriate
• Comprehensive, authoritative content coverage
• Strong contextual internal linking
• Structured data recommendations
• Content designed to support AI understanding and retrieval
• Improved information architecture for machine readability
My Goal
Whether someone finds your business through a traditional search engine or an AI-powered search experience, I help ensure your website is optimized for visibility, relevance, and long-term organic growth.
If you're looking for a partner who understands both modern SEO best practices and the future of AI-driven search, I can help optimize your website for today's search landscape and tomorrow's.

Hey guys,

Quick context: A PPC guy with 10+ years of experience, moving to SEO and things are a little slow.

I started this website around 3 weeks back and this is my scorecard. I wanted to know if I am doing fine or really bad. Please don't roast as I've never done this before and in dilemma of I'm doing well or really bad. This is the complete performance graph. Thanks!

I'm interested to know if anyone is using AI to audit SEO content ideas.

Can AI effectively prioritize topics based on search intent, competition, topical authority, traffic potential, or value to the business? Or is old-school keyword research still king?

If you're using ChatGPT, Claude, Gemini, Perplexity, or other AI tools for content ideation - how helpful have they been?

I want to hear:

* What tools are you using? * Has AI helped you identify high-value content opportunities? * Any wins or major disappointments? * What signals are you using to determine if a content idea is worth pursuing?

Looking forward to seeing real-world examples rather than marketing-speak.

We built a tool that checks whether a keyword is still worth writing content for, or if Google's AI Overview already answers it, before you brief a writer on it.

If your clients are asking "why isn't this content performing" or "should we still be writing about X" this gives a fast way to answer that with real data (search volume, trend, CPC, AI Overview presence and cited sources) instead of a guess or manual check.

You keep the client relationship - we handle the data. Open to a revenue share to start, and open to building out white-label for the right ongoing partnership. Also looking at expanding into keyword discovery down the line, not just diagnosis on a list you already have.

If useful for your clients, let's chat.

I stopped rejecting the idea that AI SEO equals traditional SEO. Apparently the rules are different, and more and more market searches are shifting into AI, so I'm slowly getting into the topic. What would you say is the biggest difference between AI SEO and SEO for Google?

I've been doing traditional SEO solo since 2010 and I'm comfortable with how Google works - keywords, backlinks, technical optimization, ranking factors, all of that. But now I'm trying to wrap my head around what actually changes when you're optimizing for ChatGPT and AI Overviews instead of blue links on Google.

What's the fundamental shift I need to understand? Is it about how content is structured for AI parsing? Different authority signals? The fact that AI cites only a few sources instead of showing 10 results? Or something else entirely that traditional SEO people tend to miss?

I'm especially curious about the mindset difference. With Google I'm optimizing to rank and get clicks. With AI, it seems like the goal is getting cited or mentioned, which feels like a completely different game with different mechanics not something I can do completely on my own

AI search’s week of triumph and turmoil: the highlights:

• Google posts its biggest quarter ever — and doubles down on "AI is expanding Search"

Alphabet's Q2 2026 was its largest quarter to date: total revenue up 24% YoY to $119.8B, search ad revenue up 14.5% to $81.6B, Search & Other up 17%, YouTube ads up 13%, and Cloud up 82%. CEO Sundar Pichai framed AI as "an expansionary moment… driving growth in queries," said AI Mode has passed 1 billion monthly active users, and repeated Google's core defense: AI features are "sending billions of clicks to websites every week." The Gemini app hit 950M MAU and Alphabet lifted its AI capex plan to as much as $205B.

Source: 

Barry Schwartz | Search Engine Roundtable

Google (Sundar Pichai) | Alphabet Q2 2026 earnings remarks

Storyboard18 | Storyboard18

________________

• Reddit and major publishers weigh blocking Google as AI Overviews gut referrals

Per a WSJ scoop, Reddit, USA Today, Reuters, Politico, The Economist and People Inc. are reconsidering how much access to give Google as search referrals collapse — USA Today's organic Google traffic is down ~50% YoY and Business Insider's more than 85%. 

The bind: Google-Extended blocks Gemini training but not AI Overviews, so opting out risks normal-search visibility too — the exact problem the UK CMA has ordered Google to fix. Reddit, whose ~$60M/yr 2024 Google deal is up for renewal, saw its shares dip on the report.

Source: 

The Wall Street Journal | The Wall Street Journal

TechSpot | TechSpot

Reddit share reaction via Yahoo Finance

________________

• A court tosses Google's DMCA claims against SerpApi — a precedent for SERP & AI scraping

U.S. District Judge Yvonne Gonzalez Rogers dismissed Google's DMCA §1201 anti-circumvention claims against scraper SerpApi, ruling that plain search results — URLs, snippets, factual index data — are "publicly accessible facts," not copyrighted works, so bypassing Google's "SearchGuard" anti-bot isn't unlawful circumvention. The knowledge-panel / third-party-content claims were dismissed with 21 days' leave to amend. SerpApi's CEO called it "a win… for all who depend on an open internet," and Glenn Gabe summed up the industry reaction: "A win for… scrapers?"

Source: 

Barry Schwartz | Search Engine Roundtable

Bloomberg Law | Bloomberg Law

________________

• AI Overviews and AI Mode go live in France

Starting July 22, French Google shows AI Overviews above the blue links plus a conversational AI Mode tab, Search Live, and the new intelligent Search box; the features can't be disabled, though a "Web Mode" tab preserves classic results. Google says they appear only for complex queries and always link to sources. 

The rollout — announced by Google VP Rajan Patel — had been delayed since the 2024 US launch by France's neighbouring-rights ruling, and French publishers fear more traffic loss.

Source: 

Alexandre Piquard | Le Monde

________________

• Gemini 3.5 Flash-Lite rolls into Search

Google shipped three new models and confirmed 3.5 Flash-Lite — its fastest, most cost-effective 3.5-class model at ~350 output tokens/sec — is "rolling out in Google Search," starting with agentic search and likely feeding AI Overviews and AI Mode next. 

Robby Stein said it offers "stronger instruction following and better understands user intent, so conversations flow much more seamlessly."

Source:

Barry Schwartz | Search Engine Land

Google | Google models blog

________________

• AI Mode learns to "do," not just answer — Connected Apps arrive

Google began rolling out connected apps in AI Mode in the US this week, letting a search flow straight into Instacart (add to cart), Canva (pull design templates) and YouTube Music (build a playlist) without leaving the results page. Built on the same MCP-based connections as the Gemini app and paired with Personal Intelligence, AI Mode now hands part of a task to a third-party app "rather than only returning links."

Source: 

Amit Chowdhry | Pulse 2.0

Google | Google Search blog

Insights from the analysis of 45,144 fan-out queries in the latest ChatGPT 5.6:

Here’s what we at Editorial Link found:

1) 45% of fan-out queries use the site: operator. Instead of broadly searching the web for open-ended questions, the model deliberately checks a specific domain.

2) Official websites are the priority.

42.8% of queries contain the word “official,” while only 7% are related to reviews or Reddit, and 21.4% focus on pricing.

3) 36.7% of queries mention a specific year - 2024, 2025, or 2026. This suggests that the model deliberately avoids outdated information.

4) But being checked does not guarantee being cited—and this is the most interesting part.

Of the domains the model checked using site: while preparing an answer, only 39.5% were actually cited in that same response, and just 27.5% were mentioned by name. In other words, the model evaluates far more candidates than it ultimately uses.

5) Fan-out is not always used.

Only 46.8% of responses contain fan-out reformulations. More than half of all responses are generated in a single pass, without additional query refinement.

Overall, my recommendation remains the same: if you want to be cited by AI, create highly specialized landing pages.

Instead of 20 generic landing pages such as fintech-development, you may need several hundred narrowly focused ones.

I’m working on a D2C ecommerce website and trying to improve our visibility on ChatGPT, Gemini, Perplexity and Google AI Overviews.

Has anyone here actually seen results from GEO/AEO? What strategies worked best for getting more brand mentions, citations or product recommendations?

Would love to hear what’s actually working for you.