GEO Content Pipeline¶
What It Is¶
The production loop that converts a prioritized prompt into content engineered to be cited inside LLM answers. It is an agent-workflow-pattern specialized for GEO:
prompt → answer-first brief → draft (validated tactics) → HUMAN GATE (facts)
→ JSON-LD schema + semantic structure → publish (.html + .html.md, sitemap, IndexNow)
→ entity hooks → enqueue for measurement
What Makes It GEO-Shaped¶
- Answer-first chunks: every section leads with the direct answer in ≤150 words; content is built as independently-extractable 50–150 word units (passages get cited, not pages — see llm-search).
- Validated tactics baked in: a statistic, a named quote, cited sources, fluent prose — the Princeton-validated winners — are brief requirements, not afterthoughts.
- Machine-parseable: schema-markup (Organization/Article/FAQPage/HowTo) plus dual-format publishing (
.html+.html.md) and an IndexNow push for immediate discovery. - Factual gate: a human-review-gate on accuracy is non-negotiable — a hallucinated spec or price is a brand and legal liability.
How It Applies to Marketing Factory¶
It reuses the content-machine for production but reshapes the output for extractability, takes its backlog from geo-prompt-research, and hands finished URLs to geo-citation-measurement. Off-page authority (content-authority) runs alongside as a parallel program. In a non-English market, the pipeline produces in-language and defines entities in-language. Drafting/schema/publish are agent-ownable; factual sign-off is human.
Related Concepts¶
- content-machine — the general production system this specializes
- geo-prompt-research — supplies the prompt backlog
- llm-search — the citation mechanics the output is engineered for
- human-review-gate — the non-negotiable factual-accuracy checkpoint
Referenced from: geo-factory-operations