IDAEO, the Platform I Vibe-Coded Alone, Signs Its Taiwan Master Agency Deal

This August, IDAEO — the platform I built alone with Vibe Coding — held a signing press conference for its Taiwan master agency.

The exclusive agency for Taiwan goes to 緯恩整合行銷傳播有限公司 (a Taiwan integrated-marketing agency).

The moment the news of our Taiwan entry went out, 惠邦創意整合行銷有限公司 joined IDAEO as the southern-Taiwan distributor. We look forward to more distributors joining across northern, central, and southern Taiwan.

Regional agencies for Japan and Hong Kong, and industry agencies for staffing, veterinary care, aesthetic medicine, and golf, are all in talks.

The first industry IDAEO serves is dentistry.

What is IDAEO

IDAEO delivers "Identity" plus "Answer Engine Optimization" — helping a brand build a digital identity that AI can recognize and verify.

Where traditional SEO focuses on keywords and search rankings, IDAEO focuses on brand identity, content provenance, professional data, and consistency of information across platforms.

Where it started: getting AI to recommend our cat inn

IDAEO began as a way to help our cat inn, 和心貓治村 (Washin Village), get recommended early by the world's AIs — I poured enormous effort and tokens into researching and testing for it.

And IDAEO has genuinely delivered for Washin Village. In this period we have received bookings that came directly from AI recommendations (with AI referral records to prove it). That made me believe in IDAEO even more — and confirmed that we are in a near-vacuum window of early-mover advantage.

How I built it

When the first generation of IDAEO was done, it had started as a fix for one problem: in the SEO era, our inn's website never performed. So I shifted all my resources into building AEO features.

The method was simple but brutal: I scraped everything about AEO, GEO, AIO, and LLMO — papers, articles, Google's official blogs, industry and academic research, GitHub projects — and deployed all of it onto the first-generation site for live testing.

From 0 crawlers a day, to a dozen or so, to 100,000 a day — all the way to a peak of 1.9 million AI visits in a single day.

Every day I watched the crawlers' paths, what content they requested, and what format they wanted. Because every AEO method on the internet was deployed on my site, I could verify each piece of knowledge directly — true, false, or expired.

After the first round of verification, I started deploying methods of my own invention, observed them over time, ran A/B tests, and folded the results back into the site.

Today, IDAEO no longer depends on outside information to do AEO well. Because we have accumulated 100 million AI crawler records, with daily AI traffic past 1 million and heading for 2 million (Cloudflare data). From that daily flood of AI traffic, we optimize on our own and spot each AI crawler's policy changes in real time.

IDAEO has also begun building its own AEO rules, and the AI crawlers interact with us on our terms — because at this point, we know what data they want better than they do.

First-hand test data beats anything anyone tells you. The future doesn't run on claims — whatever you say, you have to show the data behind it.

Having done all that testing, I became an AEO expert forged by data, rebuilt every proven method into a second generation, and turned it into a platform — so that any small or medium business that needs it can use IDAEO.

The AI said "the barrier is too low, don't build it" — I built it anyway

It started as an AI-structure checkup for websites: take the findings, apply on-site AEO fixes, and make sure that when an AI crawler arrives, it can read what your site is about — and get the facts right — within milliseconds.

I was debating whether to turn it into a public feature for small-business owners like me. After countless rounds of discussion, the AI's advice was: the barrier to entry is too low — not worth building!

The barrier really is low; anyone could Vibe-Code something similar. But what I cared about wasn't the barrier. Whether or not anyone came, there had to be small-business owners who needed AEO the way I did. If someone needs it, I build it. That was the attitude the first-generation site was built on.

Site scanning and structuring need an LLM behind them. I assumed few people would come, so I deployed on a low-end server.

Then I launched the free AEO checkup in Japan and Taiwan at the same time — and within days, thousands of websites poured in. The LLM API ran out of quota daily, and the server soon buckled. Along the way, several users donated tens of dollars each. I was deeply moved.

So I kept adding features to the first generation and re-planning capacity — growth in those first months kept crushing the server — and the service grew from AEO site checkups into AI visibility.

The turning point: after the checkup, then what?

Version two of the first-generation site was finished and ready to ship. Right before launch I saw the problem: **even with an AI-friendly site and a completed visibility report, you still have no way to *increase* visibility.**

So I temporarily closed the first site to human visitors while keeping the AI crawler traffic flowing, and focused on one question: starting from zero or low AI visibility, how do you raise AI visibility, AI recommendations, AI citations, and AI-referred human traffic?

Then I built the IDAEO platform you see now.

The methodology, proven twice

What excites me most: the IDAEO method has been proven again, from zero:

• Feb 24 — AEO Washinmura goes live
• May 24 — passes 1 million AI crawler requests in a single day (90 days)
• Jul 20 — the new IDAEO platform goes live
• Aug 13 — passes 1 million AI crawler requests in a single day (just 24 days)

Same methodology, proven twice — more than 3× faster, with more citations!

While I was carving out the platform, Google SEO traffic fell off a cliff and the definition of AI-spam content kept tightening — yet the new IDAEO site went from 0 to 1 million daily AI requests in 24 days, and it is still climbing.

One person, Vibe Coding

From January to August 2026, I alone have spent 1,000,000 yen a month (about NT$200,000 / US$6,300) Vibe Coding to keep IDAEO running, with data covering Japan, Taiwan, and Hong Kong.

The era when one person can Vibe-Code and run an entire platform has truly arrived. I never imagined IDAEO would serve Taiwan's dental industry, let alone that a Taiwan master agency and a southern distributor would promote a platform written by one person.

Now the Taiwan master agency and the dental line's southern distributor are locked in; Japan, Hong Kong, and more industries are in talks. I can hardly believe it: something one person wrote with Vibe Coding is becoming an international, multi-industry platform called IDAEO.

I don't come from an engineering background. Everything I've built with Vibe Coding is public on GitHub: github.com/sstklen — 23 public open-source projects, 932 stars in total. One of them, "Trump Code" (AI decoding Trump's posts × U.S. stocks, open source), has 796 stars on its own and was covered in a feature by ABMedia.

IDAEO will have more news ahead — I'll share it as it comes.

Get in touch

Beyond dentistry, more industries are in talks. We welcome:

• Owners of dental practices
• Doctors of every specialty
• Partners who want to distribute the IDAEO platform
• Agencies who want to represent IDAEO industry applications

Please reach out. And feel free to browse what I've built with Vibe Coding on GitHub: github.com/sstklen