AI Discoverability Case Study: Invisible to Cited in 60 Days

In early 2026, I asked ChatGPT who Shahab Papoon is. The answer was some version of “I don’t have specific information about anyone by that name.” Same with Claude. Same with Perplexity. Same with Gemini.

I was invisible. Not just to AI. To everything. I had no traditional SEO presence either. My only website was keyweemotion.com, a 3D animated experience built to blow people away when they land on it. It does that job well. I still love watching people’s faces when they see it. But for AI systems? Totally unreadable. Heavy JavaScript, no semantic HTML, no structured data, no crawlable content. I’m keeping Keyweemotion exactly the way it is. That site was built for humans.

But I needed a site built for machines.

I fixed that within about two months. Every major AI model now describes me, my work, and my affiliations correctly. And it keeps getting better every week. In February and March 2026 alone, three people found me through AI search using deep, niche prompts. One of them turned into a potential job opportunity. I’ll share more about that story soon.

Today, if you ask any major AI model “Who is Shahab Papoon?”, you get a real answer. My title, my ventures, my research, my affiliations. All correct. I even built a dedicated Who Is Shahab Papoon? page that serves as an AI-optimized identity hub, structured specifically for language models to parse and cite.

This is the build story: how I went from invisible to AI-cited in about 60 days, and how the process turned into a product anyone can use. For the technical how-to, see how I made my website AI-discoverable.

Building a Website AI Can Read

I was starting from zero on web presence. No SEO. No blog. No structured data anywhere. But I wasn’t starting from zero on content. I had a Knowledge Operating System (KOS) with all my copy, brand positioning, and content strategy already structured and documented. The data existed. It just had no home on the web.

My objective was simple: fast, lightweight, and machine-readable. Design and animations were not the priority (Keyweemotion already handles that). I’m happy with the minimalism we ended up with. I built it on Astro for static HTML output AI crawlers can actually parse. The full technical breakdown is in how I made my website AI-discoverable.

With my KOS loaded and Claude Code as my build partner, I got the entire website done in one deep afternoon session. One rabbit hole. All my data, copy, and structure were already organized in the knowledge base. Claude Code helped me turn it into pages. This is Systems Before Tools in practice.

Since I was building from nothing, I had to lay all three foundations at the same time: SEO, AEO, and GEO. They’re not separate strategies, they’re layers you build in order. This post is about the bigger picture and the journey, not the technical checklist.

The Audit Obsession

After the website was live and I was happy with the front end, I started prompting Claude Code to run audits on every aspect of AI discoverability. SEO checks, AEO checks, GEO checks, schema validation, NAP consistency, social profile completeness. You name it.

Hundreds of iterations. Not an exaggeration.

I also ran research prompts through Gemini, Manus, and ChatGPT (good ole days) to cross-reference what I was finding. Then I went to the source material. I studied the audit methodologies and product lines from the biggest names in SEO:

• Ahrefs for backlink analysis and site audit frameworks
• HubSpot for content strategy and inbound methodology
• Moz for domain authority and local SEO best practices
• Search Engine Journal for algorithm updates and technical SEO guides
• Semrush for competitive analysis and technical audit patterns
• Neil Patel / Ubersuggest for keyword research and content optimization

I studied what they check, how they score, and what they recommend. Then I filtered everything through the lens of AI discoverability. Most of these tools are built for traditional SEO. None of them check whether AI models can find and describe your business correctly.

Since I was working in Claude Code the entire time, every fix, every audit, every SOP got documented. Skills, prompts, procedures, all saved. This documentation is what made building the product possible.

From Personal Tool to Product

I want to be clear about something. I built this tool for myself. To check my own work. To validate that the changes I was making were moving the needle on AI discoverability. Every time I implemented a fix, I wanted to run a quick check: did it work? Did my score go up? Did the AI models start picking up the new information?

With every check, I built another piece of the backend. NAP consistency checker. Schema validator. Social profile scanner. AI-readiness file checker. Layer by layer, it became a comprehensive audit system.

Then I started using it for clients through ConnectMyTech. The same checks, the same fixes, the same measurable improvements. That’s when I realized this should be available to everyone.

Here’s how it evolved:

Less than two months from first prototype to live product with payments.

The public version gives you the audit, the score, the findings, and the recommendations. You can sign in with email or Google to keep track of all your audits.

My own dashboard has more features. I use it daily for client work, running audits, tracking changes over time, comparing before and after scores. The plan is to roll that out for public use soon. I’ve already scoped the build with my dev and we have a timeline.

Try It Today

The audit is live at connectmy.tech.

Run your free audit, enter your website and social links, watch six modules run in real time, and get your score with specific recommendations you can act on today. See connectmy.tech for current pricing and limits.

If you want the full picture (AI prompt testing, competitor analysis, content gaps, web presence scan, and a PDF report) you can upgrade after your free audit.

What Comes Next

This is the first post in a series about AI discoverability for specific industries. Next up: AI discoverability for consultants and coaches. Personal brands have unique challenges. Your name is your business. Entity consistency matters more than it does for a storefront. AI models need to connect your name to your expertise across every platform you touch.

If you’re a consultant, coach, or service provider and you want to know where you stand, run your free audit. Current pricing and limits are on the tool page.

Then start building. The AI systems are listening. The question is whether they can hear you.