Working session
MultipliedHQ and Agent88 aligned on GEO as the immediate collaboration lane, with Juanes sharing prior AI SEO research and product opinions next.
PRIVATE PROPOSAL / MULTIPLIEDHQ × AGENT88 GEO PILOT
Make Multiplied the agency behind the answers.
Not another SEO slide deck. A GEO operating system that shows which AI answers cite the brand, why competitors appear, and what work moves the narrative next.
Pilot at a glance
1 public-safe brand20-30 prompts3-5 competitorsdated AI capturescitation/source mapaction queueprivate reporthuman-reviewed next steps
GEO means making sure AI answer engines understand, trust, and cite the brand when buyers ask category questions.
Answer-share means how often a brand is mentioned, cited, or recommended across a sampled prompt set.
GEO Engine Prototype
MultipliedHQ x Agent88
Query
Who are the trusted Web3 growth agencies for LATAM?
Answer gap
Competitors cited. Client brand absent or inconsistently described.
Next move
Entity page + founder proof + FAQ schema + third-party source push.
Answer-share snapshotEvidence, not vibes
Competitor A74%
Competitor B46%
Target brand12%
Source gapHigh
Sample visualization only. Real reports should use dated query evidence, platform screenshots/transcripts, source URLs, and human-reviewed action plans.
Why this is grounded
This comes from the meeting, not from generic GEO hype.
Multiplied docs
SEO + LLM visibility offer: answer-first writing, entity consistency, schema, trusted distribution, and AI citation tracking.
Agent88 edge
A managed execution layer: prompt tests, evidence capture, task routing, content/schema actions, and client-facing report surfaces.
Proposed first build
A GEO proof sprint Juanes can show clients.
Pick one public-safe brand, run a tight prompt baseline, and return a premium report page that shows the opportunity in a way a marketing agency can sell.
View the meeting-journal workflow ideas01
20 to 30 prompt baseline
02
brand + competitor answer-share snapshot
03
AI citation and source map
04
entity consistency checklist
05
content/schema/distribution action queue
06
private hosted client report
Engine architecture
Observe. Diagnose. Ship. Retest.
The point is to make Multiplied faster and more defensible: every recommendation is backed by a query, a source, a model answer, and an execution task.
01
Prompt universe
Buyer, investor, customer, category, and competitor questions grouped by intent.
02
AI answer capture
ChatGPT, Perplexity, Gemini/Google AI answers, Bing/Copilot, and search snapshots where available.
03
Citation map
Who gets cited, which sources influence the answer, and which facts the models trust.
04
Execution queue
Content, schema, entity cleanup, internal links, PR/distribution, wiki/forum/source tasks.
05
Retest loop
Before/after movement, recurring evidence, monthly client-ready GEO report.
Future expansion after the GEO proof sprint
GEO is the lead wedge. These are the expansion plays.
01
Proposal / deck generation agent
Juanes described agents learning from roughly 50 proposals. Agent88 can turn that into a managed proposal surface: meeting notes + client brief + past decks → structured proposal, Google Doc, deck, or web page.
02
Agency 360 intelligence + reporting
Marketing, PR, event, sports, and crypto agencies repeat the same research/reporting loops. A shared reporting agent can combine GEO, social listening, proof reports, and client follow-up packs.
03
NIA relationship graph
The meeting surfaced the pain of losing contact context. A network-intelligence agent can capture people, intros, expertise, and opportunity fit, then suggest relevant introductions when a need appears.
Next call objective
Choose the first brand, prompt set, competitor set, and report format.
The next Juanes call should leave with a prototype brief, not just good vibes. Agent88 can then build the first evidence report around MultipliedHQ, Agent88, a public-safe crypto client or sanitized client.
Boundary: no guaranteed rankings or citations. The sell is disciplined evidence, faster execution, and better client reporting.