Last updated: July 6, 2026
On July 6, 2026 I asked Claude to review my own website, yauhenm.com — code, SEO, scripts, everything. In one morning it found duplicate structured data on two blog posts, a build script that could silently delete every live blog page, and four flagship posts wearing the wrong label. It fixed all of it, refreshed the homepage with my latest shorts, and every deploy passed a three-breakpoint QC gate before I even read the report. This is what operating with AI actually looks like.
Most people use AI to write things. I use it to run things.
My site is a hand-rolled static site — no CMS, no framework, just HTML, a blog builder script, and Vercel. It's fast and it's mine. But hand-rolled means nobody is checking my work. So I gave the checking job to the machine.
The instruction was one sentence
"Review the code, review everything in there, update it with new videos if we have some, and see what we can make better."
That's it. No spec, no checklist. Here's what came back.
What the audit caught
Duplicate schema markup on two posts. Two articles carried their structured data twice — once from the build script, once hand-written in the source. Google can flag that and pick the wrong one. In AI search, your schema is how machines read you; broken schema means being misread.
A script that could wipe the blog. My blog builder prunes pages whose source file is gone. Reasonable — until the day the source folder is empty for a dumb reason, and the prune step deletes every live post and ships an empty sitemap without a single error. One guard line fixed a failure I would have discovered from a traffic chart.
The flagship content was mislabeled. My four AI-search posts — the exact articles I want ChatGPT citing — displayed a generic "Post" label because the builder didn't know their category existed. The most important content on the site was the least identified.
Plus the small stuff: twelve orphaned thumbnails, a stale sitemap date, a canonical URL mismatch. Individually harmless. Together, drag.
Then it shipped
Finding problems is cheap. The same session fixed every item, rebuilt the blog, refreshed the homepage with my four latest shorts, and pushed. Three commits, live on production before my coffee went cold.
The part I care about most: nothing ships blind. Every deploy runs through a QC gate — the live page opened at desktop, tablet and mobile widths, every thumbnail checked that it actually loaded, every link checked that it points where it claims. Machine checks first, then eyes on screenshots. The report ends with a verdict, not a vibe.
Why a basketball player builds like this
Film review, but for infrastructure. You don't fix your defense by feeling bad about it — you watch the tape, mark the breakdowns, drill the correction. An AI audit of your own site is exactly that: tape review for your business.
I wrote before about rebuilding this site with Claude and about why classic D2C SEO is failing in ChatGPT. This is the next step: the site doesn't just get built with AI — it gets maintained, audited, and QC'd by it, with me making the calls.
The takeaway for your brand
If your site was last reviewed when it launched, it's drifting right now — schema rot, dead assets, mislabeled content, scripts with quiet failure modes. None of it visible from the homepage. All of it visible to the machines deciding whether to cite you.
You don't need a bigger team to catch it. You need a review loop that runs on demand and a QC gate that refuses to call something done until it's verified. Mine ran this morning.
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