AI Startup Marketing
When your product defines a new category, nobody is searching for it. Standard demand capture fails because there is no demand to capture. You have to position against the job your buyer is already trying to do, create the language for the category, and make sure the AI engines your buyers now ask start citing you as the answer.
The usual playbook assumes a category exists: people search for it, competitors define the comparison, and you win share with better demand capture. An AI startup creating a new category has none of that. There is no search volume for a term nobody has heard, no review-site category to rank in, and no shared language buyers use to describe the problem. If you market like an incumbent, you spend money teaching the market a word it will not use and capturing demand that is not there yet.
The work is different. You are not capturing demand, you are creating the frame in which your product is the obvious answer. That means anchoring to a job your buyer already knows they have, giving the new approach a name, and seeding that frame everywhere your buyer now looks for answers, which increasingly means asking an AI model rather than typing into a search box.
Buyers do not search for your new category, but they do search for the painful job they are trying to finish. Position as the better way to do that job, then introduce the category as the how.
Give the category a clear, ownable name and a one-line definition. If you do not name it, a competitor or an analyst will, and on their terms.
Make the status quo the villain. The fastest way to create a category is to make the existing approach visibly inadequate for the job. See product marketing.
Before spending a dollar, nail the job-to-be-done frame and the category name. Everything else inherits from this. Get it wrong and every channel amplifies a confusing message.
Write the explainer that defines the category and the job better than anyone. This becomes the source AI engines and humans both quote. See demand generation.
Optimize so ChatGPT, Claude, and Perplexity cite you when buyers ask about the job. This is the new top of funnel for technical buyers. See GEO.
Only once the frame is seeded do you layer paid and outbound, capturing the demand your own content is now generating rather than chasing demand that does not exist.
Technical and B2B buyers increasingly start by asking an AI model, not a search engine, especially for a problem they cannot yet name. If ChatGPT, Claude, and Perplexity do not mention you when someone describes the job your product solves, you are invisible at the exact moment the category is forming. Generative engine optimization, getting cited by these models, is now a core part of marketing an AI startup, not a nice-to-have. I build this into the GTM from day one and run the same play on my own brand. See GEO and GEO vs SEO.
I led growth at cnvrg.io, an MLOps platform, in the years before machine-learning infrastructure was a household category, ahead of its acquisition by Intel announced November 2020 (TechCrunch). That was the exact problem on this page: marketing a technical AI product when buyers did not yet have the language for the category. I also led acquisition at Elementor from roughly $200K to over $20M ARR and drove 337% MRR growth at Riverside. See the cnvrg.io case study and the dedicated AI startup CMO page.
From a positioning sprint to an embedded operator who runs the whole category-creation motion.
2-4 week audit of your growth stack plus a 90-day roadmap. Fixed scope, converts to a retainer.
GEO and AI-citation monitoring build.
Position against the job your buyer already knows they have, name the new approach, and seed that frame in content and in the AI answer layer. You create demand rather than capture it.
Not first. Paid amplifies whatever frame you have. Lock positioning and publish the definitive content first, then layer paid to capture the demand your content creates.
Technical buyers increasingly ask AI models instead of search engines, especially for problems they cannot name. If ChatGPT, Claude, and Perplexity do not cite you, you are invisible while the category forms.
Anchor the name to the job, keep it plain, and pair it with a one-line definition. The goal is a term buyers can repeat, not a clever brand word.
Yes. I led growth at cnvrg.io before MLOps was a recognized category, ahead of its acquisition by Intel. That is the exact motion described here.
A locked positioning and category frame tied to the buyer’s job, because every channel inherits from it. Then the definitive content and the GEO build.
A fixed-scope diagnostic sprint runs $6,000 to $8,000. Infrastructure builds start at $5,000 per month. A full embedded operator engagement runs $8,000 to $18,000 per month.
Yes. I am bilingual and run a split day covering Israeli and US hours. See AI startup CMO.
Book a 15-min call. I will give you a first read on your positioning, the job to anchor to, and whether the AI answer layer is already working for or against you.