Building the Real SEO™ Life Content Engine
How We Defined the Publishing Workflow That Turns Krisada.com Ideas into multiple content types for RealSEOLife.com
Three things became clear during the build.
What was measured.
The short version.
This case study documents the website build of the RealSEOLife.com content engine ... the workflow spec, the cross-property adaptation model, and the JSON-LD @graph system wired into every article page.
The key finding was that a downstream property does not republish canonical content.
It uses the idea as source material for multiple content types that best serves its own purpose.
What was the system?
RealSEOLife.com existed with articles, case studies, and a renderer but no documented workflow for how ideas move from their canonical source on Krisada.com into this site.
The content-engine.md file was sitting untracked in downloads/ and described Krisada.com's architecture rather than this site's.
The JSON-LD slot in head.php was wired but nothing was generating output for article pages.
The site needed a defined operating model before publishing more content.
What changed?
Started by reading the existing untracked content-engine.md and comparing it against the actual repo structure: data/ paths, normalize_article(), the article template, and the sample schema.
Rewrote the doc to match this site's real architecture.
Verified the first article (why-seo-is-becoming-ai-to-ai-communication) was already live and rendering correctly.
Built build_article_json_ld() in functions.php to generate a schema.org @graph from normalized article data and wired it into the router's article case.
Attempted a direct article copy from Krisada.com ... identified it as wrong, removed it, and updated the content-engine.md to capture the transformation model explicitly.
What did the evidence show?
Three things became clear during the build.
First The mechanics were already in place. The renderer, normalizer, router, and JSON-LD slot all worked.
What was missing was a documented model for what to publish and how to get it there.
Second The adaptation model is not just about rewriting.
A Krisada.com teaching article does not become an article here.
It becomes whatever content type RealSEOLife.com needs the idea to be:
A case study if something was built and measured.
An experiment if something is being tested, a concept if a term needs anchoring.
The content type can change entirely.
Third The JSON-LD @graph generates cleanly from normalized article data with no per-article pre-configuration.
Every article now emits five nodes automatically:
1) WebSite 2) Person 3) WebPage 4) Article 5) BreadcrumbList
Articles with an isBasedOn value in their json_ld field carry the cross-property attribution back to the Krisada.com canonical.
What can be reused?
A downstream property's job is not to just republish the canonical.
Its job is to make the idea useful in a format that fits the site's purpose.
The content engine is the workflow that enforces proper content processing at publish time.
Keep Browsing the Case Library
Move from this evidence file back into the full proof system.