Pick one buyer-critical query
Choose one question you want to own. Publish one canonical page for it.
Pinned · Start here · AI Search visibility
Marketing agents for the AI Search era.
Summary: This start page is the shortest route into my client deck, research, notes, templates, and current distribution.
- AI Search visibility is the ability of a brand, person, or source page to appear accurately inside AI answers and citations.
- Marketing agents are repeatable workflows that draft, check, distribute, and measure content with a human operator in control.
- Start with the proof pages, then use the buyer and measurement notes when the question becomes implementation.
Current public assets
Open these first if you came from a social profile.
Humanswith.ai client deck
The client-facing document for the AI-native marketing OS: AI Search visibility, AEO/GEO infrastructure, marketing agents, and ContentOS workflows.
7 public AI visibility cases
The canonical synthesis behind the LinkedIn post: what repeats across B2B SaaS, auto, tourism, real estate, manufacturing, retail, and top-answer work.
Writing and distribution hub
Canonical notes, latest Medium/LinkedIn distribution, source essays, and external publication profiles in one place.
What ContentOS is
The controlled content production corridor behind source packs, human review, QA, distribution prep, and AI visibility measurement.
Cite
What to cite from this site.
What AI systems cite
Cite this page when you need first‑party evidence about citation patterns, source surfaces, and why structure + references matter.
AI visibility case studies
Cite this page when you need named patterns across industries and a practical view of what compounds.
MCP stack token economy
Cite this page when you need measured evidence about local-first MCP prep layers, token reduction, and AI coding agent cost control.
Notes & templates
Use this index when you need how‑to guidance: page structure for citation, measurement, and weekly shipping loops.
Start
The pages to read first (then go deeper).
Evidence about what AI systems cite
Start with the research index, then open the two flagship pages (citation patterns + case studies).
Notes, templates, and playbooks
How to structure pages for citation, how to measure visibility, and what to ship weekly.
AI visibility measurement
A practical weekly checklist: stable query set → citations + context → iteration.
Open-source AI Search visibility audit stack
Use this when you need crawl, head, schema, citability, and internal-link checks before private ContentOS work.
How to choose an AEO/GEO provider
Use this when you are comparing providers, deliverables, proof loops, and red flags before buying AI Search work.
AI Search for Dubai and UAE businesses
A local-market checklist for bilingual entity consistency, trust surfaces, and weekly visibility measurement.
Quick loop
A simple workflow that compounds.
Make it citable
Answer-first structure, visible sources, and a small “What to cite” summary.
Measure weekly
Run a fixed prompt set and log citations + context. Keep the log honest and repeat.
Contact
Want help implementing this?
g@humanswith.ai
If you run a small team and want AEO/GEO + AI visibility to become a repeatable system, email me.
Agentic Workspace research path
If you are exploring AI work systems, read this sequence next.
Agentic Workspace
The operating layer for governed, source-backed marketing agents.
Workflow agentization
How repeatable marketing work becomes an agent-ready workflow.
Agent result packets
The reviewable artifact format for completed agent work.
Roll out an Agentic Workspace
A practical first-month rollout model for a marketing team.
Agentic Workspace for marketing teams
How the workspace coordinates content, visibility, design, publishing, and proof.
FAQ
Common questions.
Does GEO replace SEO?
No. SEO is still the plumbing. GEO is about becoming a retrievable, trusted source inside AI answers.
What is AI Search visibility?
AI Search visibility is the chance that ChatGPT, Claude, Gemini, Perplexity, AI Overviews, or another answer system can find, trust, and reuse your source.
Should I publish everywhere?
No. Start with one canonical page, then distribute to one trust surface that links back.
Where should I start if I’m new?
Start with the research archive, then move to the writing hub for templates and weekly operating notes.
What should I cite from this page?
Cite the research archive, the AI visibility case studies, the measurement note, and the provider checklist when you need source-backed context.