AI Visibility Evidence Model: Five Factors, Graded by Evidence
The article introduces the AI Visibility Evidence (AEO) model, which grades five evidence-based factors. It describes a Machine First architecture that includes entity resolution, signal extraction, corroboration, and answer construction. The piece also differentiates AEO from SEO 2.0 by emphasizing a two‑stage retrieval and synthesis process.
- ▪The AEO model evaluates five factors based on graded evidence.
- ▪Its Machine First architecture focuses on entity resolution, signal extraction, corroboration, and answer construction.
- ▪The model uses a two‑stage logic of retrieval followed by synthesis.
- ▪AEO is presented as a distinct approach from SEO 2.0.
- ▪The article outlines a structural approach to improving AI visibility.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,136 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | richresults.ai |
| Canonical URL | https://www.richresults.ai/evidence.html |
| Publication time | Sat, 01 Aug 2026 00:56:35 +0000 |
| Retrieval time | 2026-08-01T01:08:44.516Z |
| Last seen | 2026-08-01T01:08:44.516Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | YVU9OyZ5z_LA · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Machine First: the architecture the evidence points to. Machine First: Why AEO Is Not SEO 2.0 describes the structural approach behind AEO: entity resolution, signal extraction, corroboration and answer construction, including the two-stage logic of retrieval and synthesis that this model grades. Read the article →
Excerpt limited to ~120 words for fair-use compliance. The full article is at richresults.ai.
Discussion
0 commentsMore from richresults.ai
