Kurt is the CEO of Marshal, the Managed Agent Operations company.
Founder, Marshal
AI search is not a separate channel waiting for its own line item. It is an answer layer already draped across your entire funnel, shaping how buyers discover, compare, decide, and implement. This...
AI search is not a speculative technology bet. It is a revenue channel that intercepts natural-language intent, reduces discovery friction, and converts earlier in the buyer journey than...
The search stack has undergone a structural inversion. What began as a crawl-index-rank pipeline for sorting documents by link authority has become a retrieve-generate-cite pipeline for...
llms.txt is a lightweight, machine-readable markdown file placed at a site's root that tells large language models what a brand is, where to find clean source material, and how to cite it...
A canonical identity registry is the single, machine-readable record of who an organization is, expressed as stable identifiers, typed attributes, and resolvable links to external knowledge...
Jobs-to-be-done is the framework that strips AI search optimization down to the only two things that matter: revenue creation and cost reduction. By mapping the specific jobs that AI search...
Wikidata is the structured knowledge layer that gives AI systems the stable identifiers they need to disambiguate, retrieve, and cite real-world entities. This article explains how QIDs, property...
AI search optimization is the practice of engineering content and structured data so large language models retrieve, cite, and recommend your brand with confidence. This article introduces the...
Entity-centric architecture is the knowledge design framework that organizes all content, data, and structured markup around disambiguated entities rather than keywords or pages. Entity-centric...
Embeddings are the numerical representations that AI systems use to measure, compare, and retrieve meaning. An embedding translates text into a vector, a list of numbers in high-dimensional space,...
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