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ArchiveSep 24, 2026Est. 2025

Field Notes.

A working archive of how Marshal thinks about AI agent systems, AI search, and the operating models that make companies hard to ignore.

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Field Notes Archive

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Glyph-field title card on dark carbon: dense workflows texture glowing purple, article title "Automate Legal Intake: From Inquiry to" on staggered dark slabs.
Workflows

Automate Legal Intake: From Inquiry to Attorney Review

When a prospective client contacts a law firm, the clock starts running immediately. In legal services, responsiveness often determines whether a firm signs a desirable matter or loses it to the...

Kurt Fischman, Founder of MarshalKurt FischmanSep 24, 2026
Glyph-field title card on dark carbon: dense aiAgents texture glowing purple, article title "How to Build an Honest AI Business Case" on staggered dark slabs.
AI Agents

How to Build an Honest AI Business Case

Most AI business cases presented to business owners are built on an accounting illusion. A vendor or internal advocate tallies up minutes saved across routine tasks, multiplies that time by an...

Kurt Fischman, Founder of MarshalKurt FischmanSep 22, 2026

Showing: GEO

16Mar 2026
GEO

How to Structure Content So AI Can Actually Use It

AI-ready content structure is the deliberate architectural design of web content so AI retrieval systems can extract, chunk, and synthesize individual passages. Unlike traditional SEO, which...

Kurt Fischman · Mar 16, 2026

15Mar 2026
GEO

GEO vs SEO: The Complete Guide to How They Differ

GEO (Generative Engine Optimization) is the practice of engineering content for citation and visibility inside AI-generated responses, while SEO optimizes content for traditional search engine...

Kurt Fischman · Mar 15, 2026

06Dec 2025
GEO

How AEO Rewires the Buyer Discovery Journey

Answer engine optimization (AEO) is a discipline that remaps buyer discovery from click-based funnels to AI-mediated surfaces where large language models, AI overviews, and answer engines compress...

Kurt Fischman · Dec 6, 2025

03Dec 2025
GEO

Engineering Content for the Age of Algorithmic Literacy

Algorithmic literacy is the operational capacity to engineer content that satisfies both machine retrieval systems and human decision-makers. In an era where 40-50% of organic search traffic is...

Kurt Fischman · Dec 3, 2025

17Nov 2025
GEO

How To Place AI Search in Your Funnel Without Wasting CAC

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...

Kurt Fischman · Nov 17, 2025

03Nov 2025
GEO

llms.txt: What You Need to Know

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...

Kurt Fischman · Nov 3, 2025

03Nov 2025
GEO

Understanding a Canonical Identity Registry

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...

Kurt Fischman · Nov 3, 2025

30Oct 2025
GEO

How Wikidata Enables AI Search Optimization

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...

Kurt Fischman · Oct 30, 2025

30Oct 2025
GEO

Intro to AI Search Optimization

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...

Kurt Fischman · Oct 30, 2025

30Oct 2025
GEO

Entity-Centric Architecture 101

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...

Kurt Fischman · Oct 30, 2025

30Oct 2025
GEO

A Simple Guide to Understanding Embeddings

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,...

Kurt Fischman · Oct 30, 2025

30Oct 2025
GEO

Chunk Engineering 101

Chunk engineering is the discipline of structuring content into self-contained, semantically complete units that AI retrieval systems can extract, embed, rank, and cite independently. This article...

Kurt Fischman · Oct 30, 2025

Let's get back tothe work of humans⁠1

Machine-like is the services layer that bridges frontier AI and business operations.