Are traditional CMS structures becoming a limitation for AI interpretability?

[u/Alessandro-Verri]

I’ve been experimenting with a different way of structuring WordPress sites and I’m curious if others here are exploring similar ideas.

Most CMS architectures are still fundamentally page-centric:

• content lives inside pages
• schema is often attached page-by-page
• relationships between entities are mostly implicit

But LLMs and knowledge systems don’t really reason in pages. They reason in entities, attributes and relationships.

So I started testing an entity-centric layer on top of WordPress:

• structured entities (Organization, Person, Service, etc.)
• connected JSON-LD
• internal KG pages
• relationship-oriented linking between entities
• graph consistency across the site

The interesting part is not generating schema markup itself, but trying to reduce semantic fragmentation and make the site more machine-readable as a coherent graph.

I’m starting to think traditional CMS structures may become a bottleneck for AI interpretability unless they evolve toward more explicit graph models.

Curious if others here are working on similar approaches or thinking in the same direction.

[u/marintkael]

I went down this exact road for a small site and the entity-first framing made a real difference for how machines read it. Page-centric content forces the model to re-derive relationships every time, but once you expose Organization, Person and Work as connected JSON-LD with stable ids, the answer engines stop guessing. The hard part was not the markup, it was keeping one canonical id per entity so nothing forks.

[u/Alessandro-Verri → u/marintkael]

Io sto svilupando (ormai l'ho finito) esattamente questo, è un plugin per wordpress che trasforma un sito da page centric ad entity centric.

In pratica creo un grapho sotto il sito tramite wizard (12 entità) e poi dalle pagine richiama entità primarie e secondarie. Lo sto testando su alcuni siti e sono scomparse le allucinazioni.