Every AI company describes
itself the same way.

Your buyer has seen ten demos this quarter and cannot tell you apart. The problem is rarely the product — it is that the category language is saturated and the messaging leads with architecture instead of outcome. Story Mode helps AI startups build a narrative buyers can actually distinguish, and a funnel that converts interest into pipeline.
50+
AI & technical startups
2–4wk
To funnel clarity
20yr
In growth marketing
Trusted by founders at
GroundfloorRaiinmakerBlockonomicsBitrefillDSCVRTradeZeroStep3

What this looks like in practice.

RaiinmakerChief Marketing Officer (Fractional), 2024
Two audiences with almost nothing in common, both needed at once.

A decentralised AI network where consumers contribute video data through a mobile app and node operators run validator infrastructure. Operators evaluate the network on technical and economic terms; contributors respond to reward mechanics and community. One message could not serve both, and the network needed volume on both sides simultaneously to be commercially useful.

  • Split go-to-market into parallel B2B and B2C tracks with separate persona content
  • Ran wallet-level targeting to reach holders of specific tokens on X and Reddit, sidestepping the ad restrictions that block conventional crypto acquisition
  • Built distribution through KOL and alpha group partnerships, plus a campaign with a major professional sports franchise
  • Sustained community engagement through town halls, X Spaces, and recurring activations
Network scaled from ~200,000 to over 450,000 users

What they said.

Helped kickstart our marketing strategy from concept to new product launch.

Nick CasaresHead of Product, Step3

Deep knowledge in marketing with a deep passion about crypto. Always quick to produce results.

Sergej KotliarCEO, Bitrefill

Built for AI founders who need
sharper GTM.

01
Technical products, real buyers

Founders who can explain the architecture precisely and struggle to explain what changes in a customer’s week.

02
Demos that don’t convert

Teams generating interest and evaluations that stall, because impressive is not the same as necessary.

03
Founder-led sales that won’t repeat

Deals that close when the founder is in the room and stall when they are not. A positioning gap, not a headcount gap.

Sound familiar?

1
Your messaging leads with the model and the buyer wants the outcome.
2
Your positioning statement could be pasted onto a competitor’s site unchanged.
3
Prospects are impressed by the demo and cannot articulate why they need it.
4
The technical buyer is sold and the economic buyer has not been addressed at all.
5
Nobody senior owns whether any of this converts.

Story Mode turns technical capability into market demand — with a category narrative that holds up and execution discipline behind it.

What actually gets built.

AI startup marketing fails at translation more often than at volume. The work below is aimed at the gap between what you built and what a buyer understands they are buying.

01
Category narrative

Where you sit in a crowded market, defined so a buyer can place you in one sentence and repeat it accurately to a colleague.

02
ICP and buying committee

Who the technical evaluator is, who the economic buyer is, and what each has to believe. AI deals routinely die because only one was addressed.

03
Technical-to-commercial translation

Messaging that leads with the job and uses the technical depth as proof, so credibility survives the simplification.

04
Demo-to-pipeline conversion

The path from impressive demo to qualified opportunity, which is where most AI funnels quietly leak.

05
Content for technical buyers

Material that respects the reader’s expertise — evaluation criteria, honest limitations, real implementation detail.

06
Measurement model

A KPI framework that tells you what to scale, what to kill, and when — defensible when an investor asks.

The first 90 days.

Week 1–2
Understand the buyer

Founder interviews, sales call review, and lost-deal reasons. What buyers actually say when they decline, rather than what the team assumes they mean.

Buyer researchLost-deal reviewPositioning audit
Week 3–4
Find the wedge

The use case where you are clearly the right answer rather than a plausible one. Narrow beats broad when the category is saturated.

Category narrativeUse case wedgeICP definition
Month 2
Build the operating plan

Messaging framework, content direction, channel priorities, conversion path, and the KPI model underneath it.

Messaging frameworkCampaign roadmapKPI model
Month 3
Run it and adjust

Weekly cadence, experiments against the messaging assumptions, and iteration on what is moving deals.

Weekly rhythmMessage testingPlaybook handoff

How we work together.

Fractional CMO — AI startups

Embedded marketing leadership on a monthly retainer, scoped to a market where positioning windows close quickly.

Two to three days a week embedded
Category narrative and ICP
Technical-to-commercial messaging
Demo-to-pipeline conversion
Content strategy for technical buyers
Weekly reporting and KPI model
Optional: AI-enabled workflows
Month-to-month, no lock-in

Scoped as a monthly retainer against what the company actually needs. Reggie has personally led every one of these engagements.

Questions.

How do you market an AI startup?
By describing the outcome rather than the architecture. Most AI marketing leads with what the system is — the model, the agents, the pipeline — because that is what the founders find interesting. Buyers are trying to work out what changes in their week if they buy it. The whole job is translating one into the other without losing the technical credibility that made them trust you.
How do you avoid sounding like every other AI company?
Get specific about the customer and the use case, not the technology. Category language is saturated: everyone is an AI-native platform with intelligent agents. Nobody else has your customer's specific workflow, their specific objection, or the specific thing that broke before they found you. Specificity is the only real differentiator left.
How do you explain a technical product to a non-technical buyer?
Anchor to a job they already recognise, then let the technical detail earn its place as proof rather than lead as the pitch. The mistake is not being too technical — it is being technical in the wrong order. Sophisticated buyers still need to know what it is for before they care how it works.
When should an AI startup hire a fractional CMO?
Usually when founder-led sales is working but not repeatable — deals close because the founder is in the room, and nobody can explain why. That is a positioning and process gap rather than a headcount gap, and hiring a junior marketer into it tends to produce more activity and no more traction.
What if we are still refining product-market fit?
Then the work is learning velocity rather than demand generation: tighter experiments, clearer audience signals, and structured iteration. Scaling spend before the message lands just buys you more expensive confirmation that it has not landed yet.
Can you help with AI marketing automation as well?
Yes, and there is a useful irony in it — AI companies are often the last to apply AI to their own marketing operations. Research, reporting, and content workflows are covered on the AI-enabled marketing systems page, though positioning comes first. Automating the distribution of a message that is not working simply distributes it faster.

Building in AI and need sharper
GTM execution?

One 30-minute call. A practical conversation about why your demos are landing and your pipeline is not.

Book a Call
hello@storymode.co· Niagara-on-the-Lake, ON · Remote-first worldwide