Narrare · 3 months · from scratch
AI GTM Marketer for B2B.
A profession for people who help businesses enter new markets. You validate who to sell to and what, open the first doors, and assemble a system that brings in clients. With AI. From scratch. In 3 months.
8 companies
from EU / US · already in line for our specialists
While you're deciding whether it's worth it — companies are already writing to me asking for these people. The demand is real, not a promise.
On the job market this role is called GTM Engineer — demand for it doubles year over year, and there are almost no specialists. I don't promise that you specifically will be hired: that's the company's decision. I promise there's a seat right next to the demand.
Three marketers. Find yourself.
Starts with theory
The old marketer
“Let's draw a strategy and look at the metrics.”
A month of work, a beautiful deck — and still no clients. Looks for answers in their own head, not in the market.
Starts with tools
The marketer with ChatGPT
“Let's automate everything!”
Except it's unclear what — they don't know who they're selling to or why anyone buys. They just sped up the emptiness.
Starts by asking the market
AI GTM Marketer
Who buys? Why? What and for how much?
First the answer from the market — then a system built on that answer. Tools in hand, but the task leads. This is exactly who businesses are looking for.
Two paths. You choose in week one.
Main path
Practice at a real company
We place you in a B2B company from our queue. For three months you do this on its live business — and if it works out, you stay on with them. It's your project, your case study, and your real shot at being hired.
Second path
On yourself
Your own business, your own service, your own sales. You build an acquisition system for yourself and leave with your first working funnel.
On a regular course you learn on made-up examples and then go looking for somewhere to fit in. Here it's the opposite: from month one you work on a real business and leave with a case study, not lecture notes. This isn't free labor — it's practice on something live, like a medical residency. The project is yours, the case is yours.
How the 3 months work
Once a week — a live call, a homework assignment, and a concrete result. One skill per week. Every assignment is a piece of your final project, so by the end it's assembled on its own.
Who an AI GTM Marketer is, and your path
- The new profession: how you differ from the old marketer and from the “guy with ChatGPT”.
- The working principle: question to the market first, tools second.
- Choosing your path: a real company from us or your own business.
- How the 3 months work and how the project assembles from homework.
Homework: Choose your path, formulate the task (who / what / why), rewrite an old belief into a hypothesis.
Map of channels
- Three types of channels: fast scouts, amplifiers (ads), and foundation (site, CRM).
- Why you test a hypothesis on one cheap channel, not all at once.
- Why ads come later: they amplify what's validated, they don't search blind.
- You pick your validation channel for these 3 months and justify why.
Homework: Sort channels into the three types, pick a validation channel and explain the choice.
Market reconnaissance
- Where to find the truth about the market: competitors' ads and their clients' reviews.
- How AI gathers this picture in hours, not weeks.
- The voice of the market: what they're praised for (why people buy) and complaints (where the pain is).
- From findings to first hypotheses: who, what, and why to sell.
Homework: Analyze competitors, build a market map, write out 3–5 hypotheses.
Offer and client
- How to build an offer that grabs: short and specific.
- The client portrait: who they are, what they live by, what worries them.
- Buying triggers: the moment a person is ready to say “yes”.
- Offer ↔ client fit: check that the offer hits the pain.
Homework: Offer and client portrait on a single page under your chosen hypothesis.
List and context
- From the client portrait — clear criteria for who to search for and where to get contacts.
- How AI builds the list in hours and adds context on each.
- Triggers: AI finds who has a fresh event — changed jobs, hired for sales, raised a round, launched a product. Start with them, response is higher.
- A clean list: prioritization (who to start with) and filtering out the wrong fits.
Homework: An enriched list with triggers marked, prioritized, extras removed.
The offer page
- Why you need a page and what must be on it.
- A site from scratch: you describe to the AI what to build — no code.
- Hosting and your own domain: you publish the page and connect a “sign up” button.
- AEO: the basics so you're found not only in Google but in AI search.
Homework: Stand up and publish a landing page with booking, verify it works.
Your command center
- What a command center is and why: everything in one place.
- How to assemble a small app with AI.
- Webhooks made simple: data arrives automatically.
- Connecting sources: who wrote, who replied, what happened.
Homework: A live pipeline control panel, data arrives on its own.
Trust
- Why a cold person needs a reason to believe you.
- What to assemble: facts, a first result, a short text about yourself.
- A profile that works for you.
- How to weave trust into the future message.
Homework: A proof asset and a positioning line that the outreach will lean on.
First messages
- The structure of a message people want to answer.
- Personalization on data and on a trigger, not a template.
- The line between personal and spam + safe limits: how many per day, how not to get banned.
- Sending the first wave to real people.
Homework: Personal messages sent in a safe volume, angles fixed for testing.
Reading replies and the call
- Who replied, who stayed silent, what they're saying.
- How to read the signal: did the hypothesis work or not.
- What happens on the call: how the conversation with a lead goes and what to listen for — you're present on it.
- After the call: what to tweak in the offer based on the market's reaction.
Homework: A verdict on the hypotheses + notes from the call, what to change.
All together
- Linking it into one chain: found → messaged → caught the reply → into the command center.
- What to automate and what to keep on manual control.
- A full-loop run on real contacts.
- Where the system breaks and how AI fixes it.
Homework: One full working cycle with a real result.
Case study and what's next
- Packaging the result: what you did, what came out, the numbers.
- The case study as a portfolio and a hiring argument.
- Where to grow: what to scale after first results.
- Next channels and automation — “after validation”.
Homework: A finished one-page case study + a plan for next steps.
What a graduate looks like
A working acquisition system — on a real company or your own offer. It has run one real cycle, produced a result, and is packaged into a case study. You can explain what you did and repeat it for a new task. Not autopilot — you're at the wheel with working tools in hand.
What else you pick up along the way
Beyond the core funnel, the program quietly hands you a toolkit most marketers don't have. You learn these as you build — not as separate theory.
AI websites in 3 minutes
Spin up a site with AI in minutes, with basic AEO baked in so you're found in Google and in AI search from day one.
Competitor ad intelligence
Pull data from ad libraries in one click and read what competitors are actually running — angles, offers, creatives.
MCP for content automation
Hook up MCP connections to generate full creatives automatically — not just text, but finished visual assets.
Automated ad reports
Pull reports straight out of ad accounts on autopilot, instead of assembling them by hand every week.
Your own AI CRM
Build a basic HubSpot-level CRM from scratch with AI — one you own and never pay a subscription for.
Honest about the doubts
I'm not technical
I wrote code for years myself — HTML, Java, complex integrations. Today AI assembles the same result in hours from your description, without a single line of code. You don't need to program — you need to be able to explain what you want.
Will I actually finish?
The rhythm is weekly, and every week there's an assembled result, not “watch another video”. The project grows in pieces, it doesn't dump on you as a last-minute rush. The deposit keeps you in the game.
This is just another course
Courses don't have company demand behind them and no real project inside. You have both. The difference is between “I studied” and “here's what I built”.
The demand is already here. The question is whether you'll be ready.
There are as many seats in the first cohort as we can personally mentor. A seat is reserved with a deposit.