/ featured · this week
View all dispatches →
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
Browse long reads →
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
/ the feed · everything we've published
AI search optimization is the discipline of engineering brand discoverability, retrievability, and cite-worthiness inside large language models. AI search optimization is not SEO with new...
Kurt Fischman · Oct 30, 2025
A content chunk is a discrete, semantically self-contained unit of information that an AI system can retrieve, interpret, and cite without requiring surrounding context. Content chunks are the...
Kurt Fischman · Oct 30, 2025
Embedding optimization is the discipline of structuring digital content so that large language models locate, retrieve, and cite your brand at query time. This article explains the mechanics of...
Kurt Fischman · Oct 30, 2025
AI-native lead capture re-engineers conversion architecture for a zero-click world where large language models become the surface of first contact. This article maps the three-layer architecture...
Kurt Fischman · Oct 27, 2025
ChatGPT inclusion is not a badge or a ranking. It is whether the model surfaces your brand as a relevant answer when a user prompts it. This article breaks down the retrieval mechanics that...
Kurt Fischman · Oct 27, 2025
Answer coverage is the measurable share of prompt surface patterns in your domain where your brand appears in AI-generated answers with valid, schema-backed assets. Engineering answer coverage...
Kurt Fischman · Oct 27, 2025
AI search optimization (AISO) is the discipline of engineering content, entity signals, and structured data so that information is discoverable, retrievable, and cite-worthy by large language...
Kurt Fischman · Oct 27, 2025
Monetizing AI visibility is the practice of converting brand citations, mentions, and recommendations inside AI-generated answers into measurable business outcomes including pipeline, revenue, and...
Kurt Fischman · Oct 27, 2025
Sales attribution from LLMs is the discipline of tracing revenue outcomes back to AI-generated recommendations, citations, and brand mentions across platforms like ChatGPT, Gemini, Perplexity, and...
Kurt Fischman · Oct 27, 2025
Entity salience in AI search measures which real-world entities a document is genuinely about, not merely which terms it mentions. When salience is high for the right entities, retrieval models...
Kurt Fischman · Oct 27, 2025
An AI search optimization agency is a professional service firm built to engineer brand visibility across large language models like ChatGPT, Claude, Gemini, and Perplexity. Unlike traditional...
Kurt Fischman · Oct 27, 2025
authority-building-for-llm-credibility
Kurt Fischman · Oct 27, 2025
Trust signals in AI-driven rankings are the verifiable markers of credibility, authority, and factual consistency that large language models use to evaluate, rank, and retrieve content for...
Kurt Fischman · Oct 26, 2025
AI-era authority is the practice of making a brand discoverable, interpretable, and citation-worthy to large language models including ChatGPT, Claude, Gemini, and Perplexity. It replaces the...
Kurt Fischman · Oct 26, 2025
Measuring AI visibility is the discipline of tracking how often and where AI platforms cite your brand in generated answers across ChatGPT, Gemini, Claude, and Perplexity. It replaces click-based...
Kurt Fischman · Oct 25, 2025
Competitive intelligence in AI search is the practice of analyzing which brands get cited by large language models and reverse-engineering the semantic, structural, and entity signals that produce...
Kurt Fischman · Oct 25, 2025
Content roadmaps built for the AI search era start with retrieval fitness, not keyword volume. The traditional editorial calendar optimized for organic click-through is structurally misaligned...
Kurt Fischman · Oct 25, 2025
Wikipedia and Wikidata Q-nodes anchor entity disambiguation in large language models. When an LLM encounters an ambiguous brand name, it consults public knowledge graphs to resolve identity, and a...
Kurt Fischman · Oct 25, 2025
Multimodal LLM retrieval processes images, audio, and video alongside text. Embeddings convert visual and audio assets into vectors that retrieval systems use for similarity search, while metadata...
Kurt Fischman · Oct 25, 2025
Endpoints give LLM retrieval systems structured access to your brand data. A dedicated JSON-LD fact endpoint, properly hosted and versioned, turns opaque marketing content into machine-readable...
Kurt Fischman · Oct 25, 2025
Work at machine speed with agents on the job.