The operating system for AI-native marketing teams.
← three planes, eight domains, one operator
Three planes, eight domains, six agent archetypes, AgentOps substrate. Built on 280+ primary sources and 42 named case studies. Open under CC-BY 4.0. The standard playbook for running a Team-of-One marketing function with an agent fleet.
Eight domains, end to end.
Each domain is a standalone reference: definition, why it matters, sub-domains, best practices in 2026, tools, named case studies, common failure modes, and KPIs.
Sensing & Intelligence
Convert raw activity into structured signal feeds.
Strategy & Positioning
What to be in the market — the most agent-resistant domain.
Content & Creative Production
Highest velocity, highest brand-risk domain.
Distribution & Channel Operations
Where content meets audience — including the 83% in dark social.
AI Search & Answer Visibility
AEO/GEO/LLMO — the newest standalone discipline.
Demand & Conversational Pipeline
What turns attention into revenue.
Customer Intelligence & Synthetic Testing
Pre-launch validation, audience simulation, digital twins.
Measurement & Attribution
The mirror — without it, the rest is theater.
Where you are vs. where you could go.
click any cell to expand
The 32-cell maturity matrix maps 8 domains × Crawl/Walk/Run/Fly. Pick a domain to see its 4-stage progression: named case studies, real tools, the next move to advance, and the canonical pitfall at each stage.
Open the matrixManual baseline, no AI assist
Single-task copilots in the loop
Multi-step agents, human review
Autonomous fleet, exception-only
Ten places the framework will age.
Each frontier carries current state with primary 2026 sources, leading indicators to watch, and a practical move an operator can make this quarter.
- 01Agent-to-agent commerce + protocols
- 02Brand-to-LLM communication
- 03The Ghost Workforce labor problem
- 04Regulated-industry synthetic methodology
- 05AI-Agent Buyer Behavior
- 06The Accountability Question
- 07Saturation / Commoditization
- 08Sentiment Risk in AI Search
- 09Wikipedia Editorial Wars
- 10The Creative Quality Ceiling
Source-rigor, not vibes.
- Primary research first. Every statistic traces to a named source with a date — Conductor 2026, Jasper 2026, McKinsey, Ahrefs, IAB/BWG, peer-reviewed papers.
- Named case studies with numbers. Not "a SaaS company saw lift" — Vercel went <1% → 10% ChatGPT signups; Rootly 3% → 30% citation rate; SAP "Digital Chop Shop" $23M.
- Honest "what we couldn't verify." The "only 2% of AI SDR implementations survive" claim is flagged as unverifiable. The widely-cited "94%" Park stat is corrected to 85% (the actual paper number).
- Quarterly stat-refresh cadence. Frontiers and v4 plan published openly in
research-plan.md.