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An AI agent evaluation plan template is a fixed set of sections that turns scattered agent testing into one signed decision about whether a workflow changes hands. Eight sections carry the whole...
Aug 19, 2026/ recent · long reads
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An AI agent use case library indexes candidate workflows by the work they contain, which is a different artifact from the ranked listicle the category keeps publishing. Every list in this category...
Aug 19, 2026
Nothing about a deployed chatbot upgrades into an agent, which is why the promotion usually arrives as a rebuild disguised as a rename. A chatbot is scoped to a conversation: it matches an incoming...
Aug 18, 2026/ selected notes
All dispatches →01 / Workflows
Orchestration architecture describes the control layer that routes specialized agents through complex business workflows. Unlike single-agent systems that execute predefined scripts, orchestration...
Aug 14, 2026
02 / Workflows
Handoffs are a discipline, not an accident. Specialized agents operate reliably in isolation, but handoffs fail in production when orchestration treats state ownership as implicit rather than...
Aug 3, 2026
03 / Workflows
Agentification maturity is not measured by agent count. Start with one high-value workflow, establish guardrails and governance early, and transition ownership to the function that runs it.
Jul 29, 2026
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An AI search optimization checklist is a structured, prioritized set of on-page and entity-level fixes designed to improve content visibility in AI-generated answers from ChatGPT, Claude, Gemini,...
Kurt Fischman · Mar 16, 2026
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
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
Brand visibility in AI answers measures whether and how AI systems like ChatGPT, Gemini, and Perplexity include your brand when responding to user queries. Unlike traditional search rankings,...
Kurt Fischman · Mar 13, 2026
your-generic-schema-is-useless
Kurt Fischman · Feb 22, 2026
AI search optimization is the engineering discipline that structures digital content for citation by large language models and AI-powered search engines. It targets inclusion in synthesized...
Kurt Fischman · Feb 17, 2026
A modular knowledge object is a discrete content unit architected for machine retrieval rather than linear reading. Modular knowledge objects restructure information into atomic, self-contained...
Kurt Fischman · Dec 8, 2025
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
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
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
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...
Kurt Fischman · Nov 16, 2025
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...
Kurt Fischman · Nov 3, 2025
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
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
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...
Kurt Fischman · Nov 3, 2025
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
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
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
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
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
Work at machine speed with agents on the job.