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FORKOFF
For AI Agent Products · By application · Selective on ICP

Marketing AI agents thatmodels recommend.

FORKOFF for AI Agents is a four-surface marketing engagement for AI agent products: AEO citation, GEO surface, founder-led unedited demo distribution, DevRel motion, verified proof per dollar. Generative engines cite the agent, buyers replay the runs, builders adopt the SDK, AI funds back the next round.

Talk to FORKOFF
See the system
by application pilot floor · routes to AEO + GEO + DevRel + founder funnelBy application · 5 engagements per quarterVertical · coding · ops · voice · multi-agent platforms
4 / 4LLM platforms cited inside 60 days on a vertical SDR agent install
14Days to first unedited agent run shipped end-to-end
by applicationEngagement band per quarter (pilot floor to embedded retainer)
5Engagements per quarter (selective on ICP)
The short answer

What is AI agent marketing, and how do you market an AI agent product?

AI agent marketing runs the distribution an AI agent product has no in-house engine for: answer-engine optimization, GEO, and LLM SEO so ChatGPT and Gemini cite your agent, founder-led demo distribution, a marketing foundation, and founder funnel work aimed at adoption and the next round. FORKOFF is an outcome-priced marketing agency for AI agent products. It seeds each launch into a distribution network that has processed 5B+ qualified views, syndicates founder and product proof across creators and channels in parallel, and reports on qualified views produced rather than retainer hours.

▸ Outcome-priced on qualified views, not retainer hours. Routes across AEO, GEO, LLM SEO, marketing foundation, and founder funnel by stage. Updated 2026-07-25.

Agent shapes FORKOFF runs distribution for
Vertical SDR agentsCoding agentsAI ops agentsVoice agentsLegal AI agentsFinance AI agentsCustomer-support agentsMulti-agent platformsAgentOps communityLangChain orbitAI Engineer SummitAgent SDK buildersVertical SDR agentsCoding agentsAI ops agentsVoice agentsLegal AI agentsFinance AI agentsCustomer-support agentsMulti-agent platformsAgentOps communityLangChain orbitAI Engineer SummitAgent SDK builders
Vertical · platform · SDK builderBuilder + buyer dual-trackAEO + GEO citation per LLMAudit ledger per dollar

As Featured In

Full press shelf
By the numbers

The AI recall shift, in numbers.

AI-agent products win or lose discovery inside AI answer engines now. Here is the sourced picture behind the AEO and GEO work in this engagement.

  • Gartner projected that traditional search volume will fall 25% by 2026 as buyers move to AI chatbots and answer engines. (Gartner, 2024)

  • A page cited inside a Google AI Overview earns 120% more organic clicks per impression than an uncited page on the same result. (Seer Interactive, 2026)

  • Only 38% of AI Overview citations now come from a Google top-10 page, down from 76%, so ranking first no longer earns the citation. (Ahrefs, 2026)

  • Adding cited statistics to a page lifts its visibility in generative-engine answers by 41%, authoritative-source citations by 115%, and expert quotations by 28%. (Princeton GEO study, 2024)

  • Brands in the top web-mention quartile earn 10x more AI Overview mentions than the next quartile. (Ahrefs, 2025)

  • Google users click a traditional result only 8% of the time when an AI summary appears, versus 15% of the time without one. (Pew Research, 2025)

  • FORKOFF has processed more than 5 billion qualified views across its clipping network, the proof base behind the qualified-view reporting on this engagement. (FORKOFF, 2026)

Pre-engagement diagnostic

Why most AI agent
marketing engagements stall.

Five patterns we see when an AI agent team shops for marketing help and the engagement reads as theatre inside the first quarter. Each row is the FORKOFF fix. Read it before you book the discovery call.

fk_audit · agent_engagement_reject_log.csv
  • Row 01
    Reject reasonModel-citation gap
    Audit detail

    Buyers ask ChatGPT, Perplexity, Gemini, and Claude which agent handles their workflow. The category answer cites incumbents and open-source tooling. Your agent is missing from the recommendation.

    FORKOFF fix

    AEO citation work + answer-first long-form + per-LLM tracker. Agent gets named inside category-shortlist queries inside 60 days.

  • Row 02
    Reject reasonNo GEO surface
    Audit detail

    Generative engines pick agents to recommend based on schema, public benchmarks, and citation density. Pages with no Service schema, no published evals, and no llms.txt entry never enter the recommendation pool.

    FORKOFF fix

    GEO retainer covers schema graph, llms.txt publication, public eval pages, and per-engine citation share. Agent surfaces inside generative recommendations.

  • Row 03
    Reject reasonNo DevRel motion
    Audit detail

    Agent SDKs and integrations sell through builder trust. With no DevRel cadence, there is no LangChain talk, no AgentOps tutorial, no AI Engineer Summit slot, no docs polish. Builders adopt the agent next door.

    FORKOFF fix

    Embedded DevRel covers talks, hackathons, conference activations, and SDK reference content. Builder trust compounds into integration count and contributor PRs.

  • Row 04
    Reject reasonNo KOL coordination
    Audit detail

    AI-twitter cosigns matter for agent recall. Without coordinated KOL distribution the agent never lands inside the trusted-builder feed. Cold paid posts get scrolled past.

    FORKOFF fix

    Vetted KOL stack tuned to the agent vertical (vertical SDR, coding, ops, voice). Coordinated drops on demo cuts plus founder Q&As land in builder and buyer feeds together.

  • Row 05
    Reject reasonNo audit ledger
    Audit detail

    Demo cuts ship without traceability. Pipeline, integration signups, and contributor activity are not attributed to a specific arc, asset, or LLM citation. The agent looks busy and reads as flat to the founder.

    FORKOFF fix

    Audit-ledger receipts on cited LLMs, qualified-view share, sourced inbound, integration signups, and contributor count. Reported every Friday with the operator signature.

5 / 5 patterns auditedSource: FORKOFF agent engagement bankPre-application diagnostic
The wedge

Capability slides lose.
Agent runs that compound win.

Generic AI marketing agencies sell capability decks, sponsored posts, and horizontal blog content. Influencer marketplaces sell single-shot cosigns. FORKOFF ships unedited agent runs, AEO + GEO citation work, DevRel motion, and vetted KOL coordination so generative engines cite the agent, buyers replay the runs, and builders integrate the SDK.

14Days to first unedited agent run
30+Cuts shipped per long-form arc
5Engagements per quarter (selective ICP)
Read the DevRel wedge
LIVEAudit ledger · agent engagement bench

Three numbers that decideif an agent engagement compounds.

0 days
First unedited agent run shipped end-to-end
From scope-signed to first published run. Locked into every 30/60/90 plan.
ChatGPT + Perplexity + Gemini + Claude. Per-LLM citation share reported in the weekly report.
LLM platforms citing the agent inside 60 days
0
Pilot floor by application. Routes to AEO, GEO, LLM SEO, DevRel, founder funnel, or marketing foundation.
Engagements accepted
0/qtr
Application-only · selective on ICPVertical · platform · SDK builderQualified-view proof, audited every FridayScale-up or scale-down call at quarter end
What plugs into the agent engagement

Four phases. Twenty
deliverables behind the seat.

PHASE 01[WEEK 1-2]
01
Strategy

Agent thesis locked, vertical chosen, citation surfaces mapped.

Deliverables (5)

  • ▸Autonomy claim signed (single thesis)
  • ▸Vertical hypothesis locked
  • ▸AEO + GEO citation baseline captured
  • ▸Per-LLM citation tracker live
  • ▸Failure-mode honesty script drafted
PHASE 02[WEEK 3-6]
02
Production

Unedited agent runs, founder Q&As, DevRel artifacts in production.

Deliverables (5)

  • ▸First unedited agent run published
  • ▸Founder Q&A scoped + booked
  • ▸Schema graph + llms.txt live
  • ▸DevRel talks + tutorials drafted
  • ▸Builder + buyer cut variants locked
PHASE 03[WEEK 6-10]
03
Distribution

30+ assets per long-form, 4-platform LLM citation pursuit.

Deliverables (5)

  • ▸X demo cuts shipping weekly
  • ▸LinkedIn buyer cuts shipping
  • ▸YouTube receipts published
  • ▸AgentOps + LangChain talks queued
  • ▸Vetted KOL drops coordinated
PHASE 04[WEEK 10-13]
04
Settlement

Citation share, integration signups, ledger reported.

Deliverables (5)

  • ▸Weekly audit-ledger receipt
  • ▸Per-LLM citation share reported
  • ▸Integration signups attributed
  • ▸Contributor PR count tracked
  • ▸Scale-up or scale-down decision
What counts on the agent recall ledger

What countsas agent recall.

An agent engagement is only working when four recall surfaces light up every week. Models recommend the agent on category queries, named buyers replay unedited runs before sales calls, builders adopt the SDK with contributor PRs, and AI funds cite the autonomy claim back unprompted. Impression growth without LLM citation share does not count. The verified proof writes the four surfaces down on Friday with the operator signature.

Active check · MODELS RECOMMEND
1 / 4Recall surfaces the weekly report checks every Friday. Models recommend, buyers trust, devs adopt, VCs back.

01 MODELS RECOMMEND

Generative engines name the agent on category queries.

01

MODELS RECOMMEND

ChatGPT, Perplexity, Gemini, and Claude cite the agent when buyers ask which agent handles their workflow. Per-LLM citation share tracked weekly on the audit ledger.

fk_audit · qv_check_01

rule · Generative engines name the agent on category queries.

02

BUYERS TRUST

Vertical buyers (legal, sales ops, finance, support) replay 8-minute end-to-end runs before booking. The demo conversation starts at the second question, not the first.

fk_audit · qv_check_02

rule · Named buyers replay unedited agent runs before the demo call.

03

DEVS ADOPT

AgentOps and LangChain orbit signal compounds into installs, integration count, and contributor activity. AI Engineer Summit and hackathon traction attributable to DevRel arcs.

fk_audit · qv_check_03

rule · Builders integrate the SDK and ship contributor PRs.

04

VCs BACK

AI-fund partners cite the agent in portfolio reviews, intro warm leads, and reference the autonomy claim verbatim. Backed by founder podcast appearances and vetted KOL cosigns inside the AI-twitter cluster.

fk_audit · qv_check_04

rule · Investors recall the agent unprompted in category conversations.

Counts as verified
  • ›ChatGPT cites the agent on a category-shortlist query
  • ›Perplexity surfaces the agent in answer + sources rail
  • ›Vertical buyer replays unedited run before sales call
  • ›Integration activation attributed to a specific DevRel arc
  • ›Contributor PR opened referencing a published tutorial
Doesn't count
  • ·Generic blog impression with no LLM citation tracking
  • ·Capability-slide carousel with no demo run attached
  • ·Cold paid post with no KOL or builder cosign
  • ·Polished happy-path demo hiding agent failure modes
  • ·Backlink count growth with no buyer-LLM citation share
Outcomes the agent engagement unlocks

Citations, integrations,
and a real scale call.

Three agent campaigns across vertical SDR, coding agent, and AI ops orchestration. FORKOFF operators who owned the spine, scoped the demo cadence, ran the AEO + GEO citation work, and reported a weekly receipt the founder could read in two minutes. Read the longer write-ups inside our case-study hub.

5×

Qualified demos inside 60 days on a vertical SDR agent install. Unedited agent runs plus before-after pipeline cuts plus founder voice-over compounded into named buyer replays.

8 wk

From GitHub launch into recurring builder signal on a coding agent. Show HN spike plus 14-day clipping cycle plus AgentOps community handoff converted into compounding contributor and integration activity.

90

Days from kickoff to multi-agent narrative locked on an AI ops platform.

OWNED

You keep unedited footage, edits, masters, citation receipts, audience graph.

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operator proof

What operators say after the first quarter.

“
The qualification ledger changed how we report to the board. Real attention, verified weekly, not dashboard vanity.
G

Growth lead

Series A, 2026, AI infrastructure startup

Brand
We went from guessing pipeline attribution to seeing it in a weekly audit ledger. Finance signed off on the next quarter before the first one ended.
M

Marketing director

Mid-market, 2026, B2B SaaS platform

Brand
FORKOFF ran our conference activation across three cities in one quarter. Side events, content capture, post-event distribution. One operator, one ledger.
H

Head of events

Three cities, one quarter, DevTools company

Partner
Geo-routing pulled the campaign out of single-market mode. India and Southeast Asia carried the qualified attention count. The unit cost dropped by two thirds.
C

Campaigns lead

India + SEA launch, Q1 2026, Consumer tech brand

Brand
99.71%Sustained legitimacy rate
3.4xRetained attention vs prior agency
250+Qualified introductions
4.2MQualified views in 14 days
Featured engagements
Voices from the field

What operators say about outcome-priced marketing.

Quotes from real buyer-side teams across AI, SaaS, Web3, and DevTools verticals.

Outcome-priced changed the conversation with our board. We pay for verified pipeline, not activity reports. The audit ledger is what our CFO actually reads.

Founder and CEO

AI startup, Series A

Same budget, 3.4x more retained attention. The unit of account matters. Qualified views are the only metric we report now.

VP marketing

B2B SaaS, mid-market

FORKOFF ran our developer conference activation end to end. Side events, podcast capture, post-event clip waterfall. One operator replaced three vendors.

Growth lead

DevTools, developer conference activation

The founder funnel compounded faster than any paid channel we tested. 30 minutes a day of founder voice, 50 named accounts, weekly warm intros. Built once, runs indefinitely.

Product marketing lead

Web3 protocol

Comparison

FORKOFF agent engagement vs the alternatives.

Four routes to AI-agent recall. Match the engagement to your stage, your capital structure, and your willingness to commit to outcome-priced reporting before picking. Generic AI agencies, in-house headcount, and B2B SEO firms all lose on speed-to-first-asset and per-LLM citation transparency.

← scroll horizontally to see more →

FeatureFORKOFF agent engagementEmbedded · outcome-priced · demo-led + AEO + DevRelGeneric AI marketing agencyHourly retainer · paid + horizontal content defaultDIY in-house teamFull headcount · 6-month assemblyB2B SEO firmBacklinks + blog cadence · zero LLM citation work
Recall surfaceModel recommendations + buyer recall + dev adoption + VC backingPaid impressions + horizontal blog + sponsored postsWhatever the new VP of Marketing prefersBacklink count + Google rank position
AEO + GEO citation workSchema graph + llms.txt + answer-first long-form + per-LLM trackerGeneric SEO content with no citation receiptsDepends on the senior hires you can land in 90 daysBacklinks-first; LLM citation often unaddressed
Demo proof surfaceUnedited agent runs + failure-mode honest + founder voice-overCapability slides + sponsored posts + undisclosed bot mixTypically polished sales-enablement, no public proofNot in scope; SEO firm does not produce demos
Builder distributionX primary + AgentOps + LangChain talks + AI Engineer Summit + GitHubLinkedIn ads + horizontal newsletters; no builder trustTenure variance; depends on senior hireBacklink outreach to dev blogs; not community-based
Engagement modelEmbedded retainer, outcome-priced on cited LLMs + sourced inboundHourly retainer, output-priced on post countSalary + equity + benefits + ramp + tenure varianceMonthly retainer, output-priced on link count
Speed to first assetFirst unedited agent run in market by day 14Week 8 first generic blog post liveRoughly 90-180 days, gated on hiringWeek 4 first link placement, no demo
Reporting surfaceWeekly audit-ledger on cited LLMs + sourced inbound + integrations + contributorsMonthly dashboard with pixel-tracked impressions and last-touch creditQuarterly board deck; vanity metrics during rampMonthly link-count + ranking-position report
Agent engagement plans

Three routesfor AI agent products.

Foundation, retainer, or builder-trust seat. Match the engagement to the agent product stage. By application, capped at 5 per quarter.

01

Marketing Foundation

Positioning + ICP grid + voice guide

by application/project
  • Autonomy-claim statement
  • 3-5 ICP grid
  • Voice guide doc
  • Channel-fit table
  • Notion deliverable
Apply for Foundation
Most picked
02

Fractional CMO

Embedded retainer · operator seat

by application/qtr
  • Embedded operator
  • Audit ledger weekly
  • AEO + GEO cadence
  • Quarterly scale call
  • Pipeline traceability
Apply for Fractional CMO
03

DevRel

Builder-trust axis · SDK adoption arc

by application/qtr
  • Conference + talk circuit
  • AgentOps + LangChain reach
  • SDK reference content
  • Hackathon activations
  • Contributor cadence
Apply for DevRel

Note ·Pilot floor (by application) applies to the first cycle. Engagements scope-locked, not retainer guesswork.

Agent engagement fit diagnostic

Strong fit when 4+ are true.
Skip when any disqualifier fires.

Who you are
  • ›Shipping a vertical AI agent (SDR, coding, ops, voice, legal, finance) or a multi-agent orchestrator with paying or design-partner buyers
  • ›Founder willing to record one unedited agent run per week and front a long-form Q&A per month
  • ›Real product running for at least one paying or design-partner customer (no research-only)
  • ›Commercial moment in the next 90 days (closed beta, demo day, GA, marketplace launch, Series A)
  • ›Cares about model recall and builder trust, not impression counts
  • ›Already producing demo content but engagement is small builder circles with no LLM citation share
What FORKOFF delivers
  • ›Embedded operator who owns the autonomy-claim spine and runs weekly cadence with the founder
  • ›Unedited agent run cadence + AEO + GEO citation work + DevRel motion plugged in behind the seat
  • ›30/60/90 plan signed in week one with audit-ledger baseline captured
  • ›X demo cuts + LinkedIn buyer cuts + YouTube receipts + founder Q&As + AgentOps + LangChain talks
  • ›Weekly audit-ledger receipt on cited LLMs, sourced inbound, integration signups, contributor PRs
  • ›Routes to /services/answer-engine-optimization, /services/perplexity-seo, /services/marketing-foundation, /services/founder-funnel based on the agent stage
Not the right fit
  • ×Pre-product agents with no funded path to first paying or design-partner buyer in 12 months
  • ×Founders who will not commit to weekly unedited demo cadence (one run per week)
  • ×Research-only agents with no commercial path inside 12 months
  • ×Pure paid-acquisition mandates with no demo-led narrative or AEO citation work
  • ×Cannot show a working agent end-to-end on the first call (no live run, no recorded run)
Apply for the engagement

by application pilot floor · routes to AEO, GEO, LLM SEO, DevRel, founder funnel, foundation

FORKOFF runs the agent engagement as an embedded retainer with the FORKOFF execution stack plugged in behind it. By application, capped at 5 engagements per quarter, selective on ICP. Pilot floor sized per service stack chosen, by application. Most agent teams route into an AEO retainer, a GEO retainer, a DevRel retainer, a Founder Funnel retainer, or a Marketing Foundation project after the diagnostic.

  1. 01Sandbox
  2. 02Engagement
  3. 03Compound
By application
Apply for the engagement
Markets we run this in

Agent engagements compound where builders cluster. We anchor the cadence inside San Francisco for AI Engineer + AgentOps recall, then route enterprise distribution through New York GTM once procurement opens. How buyers surface agents in AI answers is covered in our guide on how AI Overviews rank brands.

Related lanes

Sister ICPsand routing services.

01 / 03Open

AI Startups

Sister ICP. AI-native company axis.

02 / 03Open

Dev Tools

Adjacent ICP. Developer-first product axis.

03 / 03Open

DevRel guide

Builder-trust layer for agent SDK teams.

Frequently asked questions

How is AI agent marketing different from AI startup marketing?

Agent buyers reject capability slides and reward unedited agent runs. The wedge is demo-led plus AEO citation: ship the agent run end-to-end, voice-over the failure modes, repeat at cadence, and earn citations inside ChatGPT and Perplexity for category queries. AI-startup marketing leans on founder authority and technical thesis at the company level; agent-product marketing leans on the agent doing the talking and the model citing it back. Channel weighting also shifts: AgentOps, LangChain, and YouTube long-form rise, paid social falls.

What does the agent engagement actually cost?

Engagements sized per service stack chosen, by application. Pilot floor sized per service economics, by application. Common shapes are an Answer Engine Optimization sandbox plus retainer (sandbox plus retainer), a Founder Funnel retainer (retainer, 90-day minimum), a DevRel retainer (retainer, 90-day minimum), or a Marketing Foundation project (fixed-scope project). All by application, capped at five engagements per quarter.

Do you work with pre-launch agent companies still in closed beta?

Yes, when the founder records one unedited agent run per week and a real agent is running for at least one paying or design-partner buyer. The lead wedge is Founder Funnel plus Demo Production plus AEO citation work. We start the autonomy-claim narrative before public launch so the demo lands into a primed audience instead of cold.

What does a demo-led campaign actually ship for an agent product?

An 8-minute end-to-end agent run per week, recorded unedited and voice-over by the founder. A 30-minute long-form per month (Q&A, autonomy walkthrough, ops receipt). 30+ clip variants per long-form: builder cuts on X, buyer cuts on LinkedIn, full receipts on YouTube. AEO + GEO citation work runs in parallel so generative engines name the agent inside category queries inside 60 days.

How do you handle agents that fail on demos?

Failure-mode honesty is the wedge. Buyers trust agents that show the rough edges and the recovery, not the polished happy path. We script the failure points the agent already has and frame the recovery as the proof. Pretending an agent is perfect loses every buyer who has run agents before.

Can you cover both X (builders) and LinkedIn (buyers) for agent companies?

Yes, with cuts tuned for each surface. Builders on X want product mechanics, integration depth, eval rigor, model-choice rationale, and developer-grade demos. Buyers on LinkedIn want outcome stories, vertical fit, ROI receipts, and named-customer proof. Same long-form, different cuts, different cadence.

Do you work with horizontal agent platforms or marketplaces?

Yes, with two parallel narrative arcs: builder credibility (developer trust, SDK quality, framework fit, eval transparency) and buyer outcomes (vertical wins, integration receipts, ROI). Two-sided liquidity problems need two-sided distribution. Single-channel pushes do not work for marketplaces.

What does outcome pricing look like for agent companies?

We anchor on cited-LLM share, qualified demo requests, integration signups, contributor PRs, and design-partner conversion depending on the lead wedge. Per-clip and CPM models do not apply. Vertical-agent teams typically anchor on cited-LLM share plus qualified demos. Coding agents anchor on contributor and integration counts. Multi-agent platforms anchor on builder-side and buyer-side liquidity together.

The brand line

Stop pitching agent vibes.
Ship the run buyers replay.

30/60/90 cadence. First unedited agent run by day 14. AEO + GEO citation work running from week two. Qualified-view proof from week six. Built for AI-agent products that need recall on four surfaces at once, not impressions. Pair the seat with Answer Engine Optimization, GEO, LLM SEO, DevRel, Founder Funnel, or Marketing Foundation depending on your agent stage. Browse all FORKOFF ICPs if AI agents is not the closest fit.

Talk to FORKOFF
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