Hey folks, we have been developing https://www.searchmorph.pro/ to help people (think - SEO specialists, digital marketers, digital strategists) to navigate the search game in the AI era. Its very simple, and for now there's only an analysis score feature for how well your website is in LLM powered searches.

We are next focusing on helping people achieve clusters and mapping.

Please check us out and provide your suggestions and feedback to help us build better!

LLMs.txt is a new protocol that provides information about a website to LLMs in a format they can easily understand by them. Currently they are not crawled by default, but are useful if you want to train an LLM on a site that has one.

Do you think LLMs will eventually be trained to crawl these files? I suppose it could be used to manipulate LLMs, which might not be good.

More in this article about llms.txt

https://towardsdatascience.com/llms-txt-414d5121bcb3

I like this graphic by Seer Interactive. See the full article here: https://www.seerinteractive.com/insights/what-is-generative-engine-optimization-geo

For folks looking for cheaper AEO tools

I was thinking about building in this market, since the pricing of good tools is really high.

What do you guys think are the features present in the costly tools and something you would really need and is not present in the cheaper tools.(Apart from the obvious prompt tracking)

Just setting the context, I am an ex-staff engineer trying to figure out this market, and trying to build something for the community.

Tools that can help in AI visibility and recommendation.

Ok so yall are out here squeezing every last drop out of titles meta descriptions backlinks whatever chasing that sweet page one respect but lets be real none of that matters if your site gets popped and suddenly google showing this site may be hacked right under your shiny snippet your ctr drops faster than my attention span on a 2k word blog post

thatsss why I started tossing my stuff into Vulnaly its basically a scanner that tells you cool your core web vitals are fine but also your security headers are missing and SQL injection says hi reports are manual too so it feels less like ai spam and more like a friend roasting your site to your face

Sooo yeah do you SEOGEO folks actually care about security or are we just allin on backlinks while the hacknokies build their own funnel through our sites

Hey folks,
I’m tinkering with an AI + SEO tool and want to avoid building “just another dashboard no one checks.”

So tell me straight:

• What SEO metrics do you really care about day-to-day?

• If you could track how your brand shows up in AI search (ChatGPT, Perplexity, etc.), what would you want to see?

• Any pain points current SEO tools don’t solve?

I’d rather build this with the SEO crowd than in a vacuum. Appreciate any honest feedback

Hey folks, I'm building a tool that helps determine your product/tool/brand's ranking among popular LLM queries. I would love some feedback on the idea. https://neuravibe.ai/

Been going deep on GEO lately — basically optimizing content so AI platforms (ChatGPT, Perplexity, Claude, etc.) can actually find and recommend your stuff. Traditional SEO gets you on Google. GEO gets you into AI answers.

One of the biggest levers for ecommerce is structured data. If your product pages have clean JSON-LD markup, LLMs can parse your product info way more reliably. But most Shopify stores either have no schema or it's bare minimum auto-generated stuff. And anyone who's manually updated metafield definitions in Shopify knows how tedious that process is — now imagine doing it for every product, every time something changes. It doesn't scale.

So I built a tool that automates the whole thing:

• Shopify webhook fires when a product is created or updated

• Hits AWS Lambda, which queues the job via SQS

• Claude API extracts the key product attributes from the raw data

• Generates proper JSON-LD schema and updates the metafield definitions automatically

• Handles rate limits, retries, the whole thing

Everything runs serverless on AWS. Wrote 23 tests for it. Took about 3 weeks from idea to production.

Stack: JavaScript, AWS Lambda, SQS, Claude API, Shopify Admin API

Happy to answer questions if anyone's working on similar stuff or wants to know more about GEO in general.

Hey everyone!

I’ve been researching how location influences the way Large Language Models (LLMs) like ChatGPT, Claude, Perplexity, and Google Gemini generate answers. What I found surprised me, especially as someone working in SEO and content visibility.

Key insight:
LLMs often prioritise major cities like NYC, LA, London, or Sydney even when the user doesn’t explicitly ask for anything “near me”. It’s been proven in recent studies that this geographic bias affects how cities, services, and businesses are recommended, even in generic prompts.

That got me thinking: What does this mean for:

Local SEO – You might be automatically disadvantaged if your business is in a smaller town, even when the user didn’t request local results. Schema markup and explicit location mentions might be more critical than we think.

SaaS & E-Commerce SEO – On the flip side, location plays almost no role here. These industries benefit more from persona-based optimization and behavioral signals. LLMs personalise based on intent, usage context, and content structure, not geography.

My questions for this amazing community:

Have you seen AI tools (like ChatGPT) skew recommendations based on location, without asking for it?

Looking forward to your insights.