Adoption programme for companies with 50+ employees
Computer work is simple micro-conveyors
Modern AI can already handle most of them.
One workday for anyone using a computer consists of dozens of these micro-conveyors
There is only one question: who will automate these conveyors in your company — your people, or your competitor's expensive contractor at some point in the future.
What people who work at computers actually do
Look at any workday. A phone call: information enters the brain through the ear, gets processed — and an answer comes out through the mouth. A messenger notification: someone reads it, searches for something online, adds something — then replies or forwards it.
The pattern is always the same: information in → thinking device → processed information out. These micro-conveyors make up an entire workday. And today, the "thinking device" in most of them can already be replaced with AI.
Full AI Adoption Across Your Company
$14,999
for all three stages · paid stage by stage
See what's included ↓This is what the company of the future looks like
sees the entire company as a map of automations and sets the direction
has 10–20 automations of their own and is responsible for improving, maintaining, and replicating them
automate their own work and bring their departments along — that is their job
Maintaining, improving, and replicating their automations is the new job of everyone who works at a computer.
The simple math that decides everything
micro-processes exist in an average company with 50+ employees — and sometimes as many as a thousand
is what an external integrator charges for ONE automation
is what it costs to automate 500 processes through outsiders at $1000 each. Most companies cannot afford this
And not automating isn't an option: one of your competitors will do it. A company that has automated works more cheaply, quickly, and effectively — it can charge a lower price and win customers.
That leaves one path: automations are built by people inside the company — those who know their work from the inside. They just need hands-on guidance and training.
Why not programmers
The ability to work with AI agents is a management skill, not a programming skill. A programmer works from a specification: they build the first version, perhaps a second — and deliver it. But a head of sales, logistics specialist, or accountant automating THEIR OWN work goes through 20–50 iterations — until they say at five in the morning: "That's it, great, now it works." Because the problem affects them, and they know the exceptions in their process better than any specification could describe. A company does need programmers — one or two nearby to help with servers and access permissions. But they must not be allowed to automate business processes instead of the people who perform them.
How adoption works
It all starts with the founder — every implementation that actually happens is driven by them. Their enthusiasm is then taken up by top managers, followed by proactive employees. In that order. Each stage is paid for separately: you start with the first, then decide whether to proceed with the second and third after seeing the results of the previous stage.
The founder builds three automations themselves
Every implementation that has actually happened has been driven by the founder. So this is where it starts: over five sessions, you build at least three automations for your company yourself and understand how it all works — what AI can really do and what is just fiction. After that, you no longer need advisers: you understand how it works for yourself, and there is no stopping you.
- →"Right, now do the same for my top managers" — we move on to stage 2.
- →"I already feel able to train my team myself" — you continue on your own, with the method and your own examples.
Strategy sessions: the top team adopts a new way of thinking together
Before the start, there is a recorded 4.5-hour course and three bonus lectures. Then everything is live: we examine which tasks consume each manager's time, and everyone builds 1–3 working automations with their own hands — not a training example, but a tool for their work. The others watch a neighbouring department being automated and learn from the experience: everything is built by their colleagues, right before their eyes.
- →"We will train our employees ourselves from here" — the programme ends at this point.
- →"Provide the same training for our people" — we move on to stage 3, working with proactive employees.
Proactive employees: the talent pool
In a typical company, up to 20% of employees would like to automate their work but don't know how. They watch the recorded lectures (and yes, they do watch them), and during the live sessions we take what causes the most pain and build automations live. In the admin panel, the manager can see everyone's progress and which projects each person has chosen. Experience shows that one automation built by a frontline employee covers the cost of any training — and a group of 20 usually has two to five such people.
Full AI Adoption Across Your Company
for all three stages · paid stage by stage
- ✓stage 1: the founder (with an assistant, if preferred) builds three automations themselves — 5 sessions of 3–4 hours
- ✓strategic sessions for 5–10 top managers — 10 sessions of 2 hours + a recorded 4.5-hour course and 3 bonus lectures
- ✓up to THREE groups of 20 proactive employees — available for use over one year
- ✓all sessions are recorded and added to participants' accounts; lecture access lasts one year
- ✓manager's admin panel: each participant's progress and the projects they are implementing
You do not need to pay everything upfront: an invoice is issued before the start of each stage, and you decide whether to proceed with the next one after seeing the results of the previous stage.
For comparison: an in-house AI director costs about $3,750–7,500 per month, if you can find one. Automation built by outsiders costs hundreds of thousands of dollars and creates permanent dependence on a contractor. Here, you pay once — to launch an internal adoption system.
Who leads the programme
Yaroslav Maxymovych — founder of AI Advisory Board. He was the first person in Ukraine to sell an internet startup for more than $1 million — Forbes covered the story. He founded dozens of companies: five became leaders in their niches, and he sold four. 4 600+ hours of hands-on AI experience and 29 business implementations.
Every participant in his programmes leaves not with notes, but with their own working automation, built with their own hands.
Honest answers to difficult questions
"$14,999 — that's expensive"
Compare it with the alternatives: automating a company through outsiders costs $500–2000 per automation, meaning hundreds of thousands of dollars for the full scope. An in-house AI director costs $3,750–7,500 per month, if you can find one. Here, you pay once — and the company then continues to automate itself. And you do not need to pay the full amount upfront: start with stage 1, then decide about the remaining stages afterwards.
"The team will complete the training and won't use AI"
That is why the programme starts with the founder and managers, not with a "course for everyone": each person builds an automation for their own real task, live, with their own hands. People don't abandon a tool that already saves them hours every week. But training doesn't replace management — continued use also depends on management attention.
"AI is unreliable and can make mistakes"
Yes, it can. That is why it isn't placed in critical processes without oversight. The team learns to identify where human review is required, limit the scenario, and avoid assigning AI decisions where the cost of an error is unacceptable.
"We have programmers — they'll do it"
A programmer works from a specification: they build the first version, perhaps a second — and that's it. A person automating THEIR OWN work goes through 20–50 iterations until they say at five in the morning, "That's it, great." Because the problem affects them, and they know their process better than any specification could describe. Programmers are needed — one or two nearby for servers and access permissions. But not instead of the person doing the work.
"Managers don't have time for this"
Systematic adoption is impossible without them — a contractor doesn't know the processes as well as the people who perform them every day. The format accounts for this: all training uses the participants' real work tasks, so the time isn't spent "on a course" but on automating their own work.
"Why training instead of a ready-made solution?"
A ready-made solution covers one stable process. But a company with 50+ employees has hundreds of such processes; they vary across departments and constantly change. The programme creates not one automation, but the company's ability to independently identify, launch, and maintain the next ones.
The first step — a 30-minute call with Yaroslav
You'll determine whether the programme fits your company's scale and readiness, and which of your processes will produce the fastest return from AI.