Genesis measures AI recommendation systems.

Genesis tracks how language models and vision systems perceive products, rank categories, and quietly shape commercial discovery.

Ongoing and dated. Built from primary sources: live shopping conversations, model outputs, and routing evidence.

Each report is a different lens on machine taste and machine perception.

Together they form a growing map of the systems now mediating product discovery, with a focus on what breaks, what gets privileged, and what brands can actually control.

Research papers
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PaperAesthetic consensus

Genesis 02: LLMs’ favorites.

Maps how leading language models converge on the same designers, garments, and fashion narratives when taste is inferred from prompts alone.

Plain-language answers for ecommerce teams.

Each article takes one question store owners ask us and answers it with the research — dated, sourced, and kept current as the systems change.

Articles

What these studies are really measuring.

Beyond raw outputs, the work is about the recommendation systems hidden inside current models: the assumptions they make, the aesthetics they overfit to, and the commercial surfaces they now influence.

Perception

Can a model actually distinguish brand, season, and design family from the image itself?

Preference

Which objects and creators recur across models when taste is generated from text?

Visibility

How likely is a brand to be named in AI-mediated shopping?

Reliability

Does the model know when it does not know, or does it hallucinate authority?

Genesis 03 turns recommendations into measurable routes.

The latest report studies what happens after AI systems name a brand: whether shopper demand reaches an official product page, leaks to a third-party seller, or stalls without a usable buy path.