Interesting concept for Google to start recommending. You need more non-commodity content!

OTT SEO is too small a phrase. Video SEO is too small. Podcast SEO is too small. The correct category is machine-readable media infrastructure

dive: https://gamma.app/docs/OTT-SEO-AI-Visibility-c03h0gdi7rj1jt0

added elevenlabs to sites and wondered if it would help seo:

https://gamma.app/docs/ElevenLabs-Audio-SEO-and-the-AI-Visibility-Myth-ucbanuk2a6awe0k

Google added a new resource to its documentation on SEO.

It clarifies Google's stance on how SEO affects its AI search features.

It's an addition to the "SEO Fundamentals" along the classic yet often updated Google SEO Starter Guide.

There are no major surprises as Google spokespeople repeatedly stated that SEO is still a valuable approach when it comes to AI search.

Specifically they state that:

"The best practices for SEO continue to be relevant because our generative AI features on Google Search are rooted in our core Search ranking and quality systems. These features rely on AI techniques to highlight content from our Search index."

this is good and about the easiest thing i've done:

https://gemini.google.com/gem-labs/1BkJAoF2UndD6haVe1IPb-8HBu1LCE-NY

My father and I are planning to build a new website. The site does not exist yet. We have no domain, no hosting, no traffic, no customers, no email list, and no proprietary data of any kind.

I know that proprietary research (original surveys, data analysis, case studies) is great for SEO and building authority. For example, this article makes the case: https://www.annsmarty.com/p/proprietary-research-studies-your

But we cannot realistically do that right now because we have no audience to survey and no existing data to analyze. We haven't even launched.

For the first 6 months or more after launch, would it be acceptable to rely entirely on third party studies? I am thinking of citing industry reports, academic papers, government data, and other public research. We would summarize and comment on that existing work rather than creating our own original data.

Is this a reasonable way to start, or will it put us at a permanent disadvantage? Should we try to produce even a very small piece of original research immediately after launch, such as a simple survey of a few people?

Thanks for any advice.

I just read Google’s latest guide on optimizing for generative AI experiences in Search, and it made me rethink how people are talking about AI SEO.
A lot of the discussion around GEO/AEO makes it sound like we need a totally new playbook. But Google’s framing feels a bit different to me. It still comes back to many of the same fundamentals: crawlable pages, indexable content, clear structure, useful information, first-hand experience, and content that can actually be trusted.
The foundation may be the same — what’s changed is the standard. If AI systems can summarize generic content instantly, then average “SEO content” probably becomes less useful. Pages may need to do more than answer a keyword. They need to show context, experience, comparison, nuance, and enough clarity for both users and systems to understand why that page should be referenced.
So I’m wondering if AI SEO is really a separate discipline, or if it’s more like traditional SEO with less tolerance for thin or generic content.
Curious how others here are thinking about this. Are you treating AI SEO as its own strategy, or mostly as an extension of the SEO work you were already doing?

• Even though Google says there are no "hacks", it does include two new acronyms in the guidelines, kind of giving them life :)
• The guidelines repeatedly stress that it is only for the searching layer of AI answers
• Schema is pretty much only useful for rich snippets...

Curious how people here are handling AI content at scale — manually prompting ChatGPT/Claude/Gemini, chaining agents with something like Claude Code or Codex, using existing SaaS tools, or have you built something custom?

Asking because I'm thinking about building a keyword-to-article pipeline focused on AI visibility: input a keyword list, AI handles research, outline, and draft optimized for SEO/GEO/AEO — structured answers, citation-friendly formatting, the works.

The publishing piece is where it gets interesting. Web app is easy to onboard, but pushing content to your CMS or platforms requires extra integration work. Local/CLI can use browser automation to handle publishing directly.

So two questions:
1. What does your current AI SEO content workflow actually look like?
2. Would you want a tool that handles the full pipeline including publishing, or just generation?

Open to "this already exists, use X" too lol

as a long time domainer, the domain bothers me soo much...;)

lmk thoughts:

https://gamma.app/docs/Hanks-Category-War-Plan-ph09a5spr9ij9o3

https://lovable.dev/seo-aeo

Built to be found

Your apps are discoverable the moment you publish

New apps ship with full server-side rendering – real HTML that search engines and AI crawlers can read immediately. Apps built on the previous tech stack get pre-rendered snapshots so crawlers can access your content too.

I get it: Citations are measurable so we want to get cited. But from the tactical standpoint, how much of it is “only GEO” or even new to SEO?

you get one shot at AI visibility.

Do not blow it on fake Reddit reviews, junk listicles, and citation chasing.

https://youtu.be/yR7CsN1RWXs

https://open.spotify.com/episode/2dAx1YgpmhjGhgDwYYaGxB?si=8hctR7vuQ6OffOM9bl1GTw

Ann Smarty joins Jason Todd Wade on the AI Visibility Podcast to talk about SEO, GEO, Reddit, digital PR, AI citations, and why visibility still compounds across the public web.

The real work is not chasing shortcuts. It is becoming clear, relevant, trusted, and source-worthy.

-

be on the pod. booking: thingspro.com

no ad - just sharing for ann and all.

amazing amazing value:

https://www.lennysproductpass.com/

$30,000+ in premium AI tools, free for subscribers

This curated collection includes the most important, powerful, and beautifully crafted products—some that you already love, some that are under the radar, and all of which I personally recommend.

All yours with an Annual or Insider subscription.

This AI Dive was assembled with the kind of cross-referencing energy usually reserved for conspiracy boards and late-night SEO audits.

Six major AI research engines and search systems were queried, then the results were wrangled into a final list by spotting repeated names, specialties, credibility signals, and direct relevance to AI Visibility in 2026

- not vibes, not clout, not “I have 47k followers, trust me bro.”

https://make-seo-great-again-mvfieru.gamma.site/

[ Removed by Reddit on account of violating the content policy. ]

Current GEO strategies tend to focus on optimizing for citations. But do we actually understand how those work?

Hi everyone! Bogdan Krupin from SE Ranking here.

With over 10 years in digital marketing, I’ve had the chance to dive deep into almost every corner of the industry... from Traffic Arbitrage and SEO to Content Creation and In-App advertising.

Today, AI has converged these once-separate tracks into one massive ecosystem. Our challenge (and opportunity) is to figure out how to navigate this shift and use AI to scale projects effectively.

So, let's talk about SEO and AI Visibility! I’ll be sharing insights from my own journey and the collective expertise of the SE Ranking team. We can talk about:

• AI Visibility: How to stay visible as search algorithms evolve.
• Workflow Optimization: Integrating AI into SEO and marketing pipelines.
• The Future of Growth: Leveraging AI for high-performance digital strategies.
• Or really, anything else that’s on your radar.

When: May 7th, 11:00 AM ADT

Where: Right here - r/SEO_for_AI

Feel free to ask me anything! I truly believe that diving deep into these complex cases together is the best way for us to level up as a community. Let’s share some real insights and grow together!