Glossary — the map's vocabulary

Load-bearing terms and the structural concepts the modules assume. Volatile specifics (tools, stats) are dated and tracked in the live evidence ledger.

Structural concepts (how the map is built)

• Discipline-primary spine — the map's top-level organizing axis: the 16 disciplines (A–P), not the funnel/PESO/lifecycle. Chosen because it's the only axis where a single domain is a shippable slice and boundaries match real teams/tools/budgets.
• Type-dependent organizer — the resolved finding that each domain's internal spine differs by domain type: some disciplines run on a decision axis, others on a graded property, an audience lens, or a craft-taxonomy × governance-gate (a few are two-natured). The "one decision axis per domain" rule was deliberately not locked as universal — un-primed tests broke it. (Which organizer governs a given discipline is worked through in that discipline's chapter.)
• Human↔agent audience lens — the lead secondary lens applied in every domain: who/what is being marketed to — humans (B2B/B2C/DTC) or agents (B2A/A2A). Promoted to a full domain (L) only where the agent pole earned distinct components; elsewhere a lens.
• Continuous threads (4) — concerns that run through every domain, each with a home domain that owns the methodology: brand (B), data/measurement (I), compliance (K), budget/unit-economics (A). Pattern: home owns the method; every domain owns the application. ("AI" is deliberately not a thread — it decomposes into the human↔agent lens + the maturity lens + domains J/L.)
• Funnel-as-lens — the customer-journey funnel was demoted in all 16 domains (it's non-linear under AI discovery, loops in lifecycle/community/commerce); kept only as a minor lens where work is genuinely stage-shaped.
• AI-maturity (dated lens) — manual → automated → agentic; a fast-decaying lens (lives in the ledger), never a structural spine.
• The hedge / leading re-test trigger — the map is discipline-primary now but built to flip toward agent-primary if agents become the dominant buyer; the trigger = autonomous-agent-completed order share (watch 5% / trigger 10%), currently dormant because ~70% of AI traffic is referrerless and unmeasurable.

Audience & agents

• B2A (business-to-agent) — marketing to/through the AI assistants that discover, evaluate, and buy on a person's behalf.
• A2A (agent-to-agent) — the seller's agents transacting/negotiating with the buyer's agents.
• Agent-as-operator vs agent-as-audience — an agent that runs marketing work for the brand (e.g. an AI service agent) vs. an agent that is the recipient of marketing (a buyer's agent). Several domains have both poles.
• Agentic commerce — agents completing purchases; rails incl. UCP (Universal Commerce Protocol, Google/Shopify), ACP (Agentic Commerce Protocol, OpenAI/Stripe), AP2 (Agent Payments Protocol, Google→FIDO), Web Bot Auth (agent identity).
• Machine-eligibility — being structured/feed-complete enough for an agent to retrieve, understand, and select you (Domain L's supply-side play).

Search & discovery (E)

• SEO / GEO / AEO / LLMO — link-list optimization (SEO) · being cited in AI answers (GEO/AEO = generative/answer-engine optimization) · optimizing for LLMs (LLMO). The map organizes E by retrieval-mode (link-list → answer-synthesis → agent-selection), not by these labels.
• Zero-click — searches resolved without a click to an external site; the dominant 2026 reality that makes GEO "influence without a click."
• Retrieval-mode — E's organizer: what is retrieving and what it returns.

Measurement (I) & the discipline

• Incrementality is the arbiter — the load-bearing rule: no platform-reported ROAS/lift/deflection number is a fact until an independent holdout/geo-test confirms it (platforms over-attribute ~20–60%). Anchored to peer-reviewed economics (Lewis-Rao, Gordon et al., Ghost Ads), not vendor decks.
• EMV (earned media value) — banned as a success metric (vendor-favored, no standard definition); use incrementality/MMM/self-reported attribution.
• MMM / MTA / DDA — marketing-mix modeling · multi-touch · data-driven attribution; the layered stack (MTA daily / MMM strategic / incrementality arbiter).
• Signal loss — the post-cookie/ATT erosion of identity-level data that I organizes around (basis-of-truth × signal-integrity).

Paid, partner & the rest

• Buying-model × mediation — F's organizer (manual/auction → platform-automated → agent-mediated paid); channels are a catalog, not the spine.
• Rail-control / surface-strategy — L's organizer (walled-garden vs platform-controlled vs neutral-syndication vs standards-body vs crypto rails).
• Create-vs-capture — N1 (affiliate) organizer: does the partner create demand (content/creator, incremental) or capture credit on existing demand (coupon/cashback, low-incremental)?
• PESO — paid/earned/shared/owned; a minor classification lens, not a spine.
• The four-way agent-surface rule — for llms.txt/schema/MCP on owned surfaces: C authors · D/P hosts · E specifies citability + owns the efficacy verdict · L defines commerce semantics.

Production

• Dual mandate — every module must both ADVISE (decision logic) and RUN (executable workflow). One without the other fails the build-spec.
• Locked baseline vs living map — a frozen v1.0 baseline the published edition is built against, versus the living copy that is re-grounded on a cadence.