the structured data issue that kept our site health stuck at 92%, how swapping models fixed it fast, and a founder-ready seo checklist.
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By Enzo Sison - Founder, Prism
We hit a structured data bug that would not die. Multiple fixes, multiple Semrush crawls, and site health stayed around 92%. One model switch turned it into a 20-minute win. Here is the story, the lesson, and a checklist you can use.
Video breakdown: the live walkthrough sits below. This post adds context, lessons, and the exact playbook.
I run Prism, a web studio for founders who care about growth, not just pretty pixels. Every project ladders up to three levers:
Technical SEO (opens in a new tab) sits in the middle. If your site is hard for Google to understand, you cap all three.
We were working across a 120-page site (our own plus some client work). The loop was simple:
Except it did not. Health stuck near 92%. A handful of structured data errors refused to clear. Every time we shipped a fix and waited another 20-minute crawl, the same issues returned.
We were using OpenAI (opens in a new tab)'s Codeex model through the CLI to debug:
After a couple of days, it was obvious we needed a second opinion from another model.
Structured data (schema) tells Google exactly what is on a page:
When it is implemented correctly, you get richer search (opens in a new tab) results, better eligibility for AI search (opens in a new tab), and a clearer picture of your business. When it is wrong, you get warnings, missed visibility, and less trust from Google - real revenue left on the table for a 120-page site.
I had hesitated to add Claude Code (opens in a new tab)'s Pro plan because we were already spending about $200 a month on OpenAI and had paid for Anthropic (opens in a new tab) and Gemini before. But this bug overstayed its welcome, so we tested Claude Code for roughly $20.
We fed Claude the exact same inputs we had given Codeex - Semrush error details, code snippets, and schema context. Claude spotted the underlying mistake, suggested a fix that matched the spec, and we implemented it.
We ran another Semrush audit:
The takeaway is not that one vendor "won" forever. Being dogmatic about a single model wasted days; being flexible solved it in one shot.
The AI landscape moves too fast to bet on one vendor. Your team should switch between OpenAI, Anthropic, Gemini, and whatever works best for the problem. Treat models like interchangeable power tools, not religions. If an agency insists one tool is "best at everything," that is a red flag.
Codeex gave plausible fixes that passed its own reasoning but failed reality. Claude gave a fix that matched the schema spec and Semrush's behavior. Good AI workflows stay grounded in real-world feedback (Semrush, Search Console, analytics), generate options, and test until the bug is actually gone.
A five-page brochure site can get away with a lot. A 50-200+ page site that should feed you leads daily is a different game. You need clean site health scores, structured data coverage, and crawl/indexability dialed in - especially if you are paying to send people to the site.
Answer honestly:
If you are nodding along, you likely have hidden technical issues costing you money every month.
This work is not magic. The video shows the exact issue, tools, and outcome in real time so you can see what is happening under the hood and the level of care you should expect from whoever owns your site.
If you are a founder with a site that should be producing leads - and you suspect hidden technical debt is holding it back - let us handle the ugly parts.
We will run a site health and structured data audit, fix the high-impact issues, and turn your website into something that supports your growth targets. Worst case, you get clarity on what is slowing you down. Best case, we unlock traffic and revenue you are currently leaving on the table.
If you want a full diagnostic, start with our seo audit service.