What you learn
What you learn here, no one teaches.
Not tools, tutorials or theory, and not a fixed curriculum. You learn how a business is really built and really run: the raw industry insight, the economics that decide whether something lives or dies, and the judgement to use AI where it actually matters. You learn it from inside live companies, next to the people who run them, where the stakes are real, and the work is shaped to what you want to build.
The real thing, not a version of it
The insight no classroom can hand you
Almost every programme teaches business from the outside: sanitised case studies, tidy diagrams, and people who have never built one. Here you are on the inside of real companies, and you see what is normally kept behind the curtain. This is the part that is genuinely hard to get, at any price, anywhere else.
Raw industry insight
How a sector actually works, not the version in a textbook. What really moves the money, what quietly breaks, and the things people inside a business know that outsiders never get to hear.
The decision-makers themselves
You work next to founders and operators who run real businesses, not lecturers describing them. You get to ask the questions a case study can never answer.
How the economics really work
What a process costs, what a customer is worth, where the margin sits and where it leaks. The real numbers behind a business, not a tidy diagram of one.
How a business is built from zero
The group builds ventures for a living. You see one assembled, funded and taken to market up close, including the ones still at a pre-revenue stage, with nothing dressed up.
Where the real stakes are
You sit inside live businesses where real money, real deadlines and real decisions carry real consequences. You see how a choice lands when something is genuinely at stake, not in a simulation built for your benefit.
What training keeps hidden
A training session never shows you the real failures, the real numbers or the real decisions. Here they are the material, because the environment is real and nothing is simulated for your benefit.
Weigh it honestly
A degree, an internship, going it alone, or this
There are four ways to learn how business and AI really work. Three of them cost you years, money or both, and still leave the real thing out. Here is the honest comparison, and why twelve weeks here is the least wasteful of the four.
A degree
Years and real money for theory.
- Three or four years, and often real debt.
- You leave with a certificate and almost no sense of how a company is actually run.
- The syllabus is years behind the tools people actually use.
An internship
A junior corner of the business.
- A token wage, and quietly treated as someone who waits to be told what to do.
- A permanent job is implied and rarely arrives.
- You fetch, format and file, and you see a corner, never the whole.
Going it alone
Real lessons, bought the hard way.
- You can just start something, and the lessons are real.
- But you learn by expensive failure, with no mentor and no environment.
- Nobody tells you the hard parts, so they cost you years.
This programme
Years of exposure, compressed into one quarter.
- Twelve weeks inside live businesses, next to the people who run them.
- The economics, the decisions and the mentors are in front of you.
- You keep everything you learn, and you are free to go build your own.
None of the other three gives you the insight, the people and the economics together, in one quarter. That is the whole point, and it is why the twelve weeks are worth what they cost.
Growth over comfort
Built to push you, not cushion you
We could make this far easier to say yes to. A stipend, a job at the end, a ‘learn and earn’ line on the brochure. We refuse to, on purpose. Those are promises of safety, and safety is exactly what keeps people where they are. It is what a worried parent wants for you, and what most programmes quietly sell. We think it is the wrong thing to want.
A career worth having is built by stepping out of your comfort zone, not by being insured against it. The point of these twelve weeks is to build real capability, something you can actually do, not another line on a CV. Most ‘experience’ is decoration: a title and a date that prove nothing about whether you can look at a business and rebuild it. We are not here to help you collect more of that.
It is the same reason we select on ability rather than on who can pay, and the reason there is a fee at all. The fee removes the ambiguity: it makes you an investor in yourself rather than cheap labour, and it filters for people serious enough to use the access well.
No safety net, by design
No job, no stipend, no ‘learn and earn’. Those sell comfort; we would rather you grew.
Capability, not a padded CV
You leave able to do something real, not with one more hollow line of ‘experience’.
The fee removes the ambiguity
Selected on ability, never on ability to pay. The qualifying test costs nothing, and if you are not selected, you pay nothing.
What you walk out able to do
Not another tool. The one skill that is now scarce.
The scarce skill is no longer a technical one. AI can now write the code, run the numbers and draft the documents well enough that someone who understands a business problem can reach a working answer without being a specialist in any of it. What is scarce, whatever you studied, is the person who can look at how a company operates, find where time and money leak, and rebuild the process with the tools now available. That is what you learn to do here, and you can come from any degree.
Read how a company runs
See the functions, the handoffs between them, and the exact points where a process loses time and money. Most people never get this vantage until years in.
Build the answer without code
Assemble a working tool with AI, for a step you mapped yourself. You do not learn to program; you learn to turn a business problem into something that runs.
Know where AI can be trusted
Where an autonomous system can be left to act, where it cannot, and how to put the guardrails around it. That judgement is the scarce thing, and it is only built in a real environment.
Prove it in money
Quantify what a process cost before and what it costs after. You leave able to make the commercial case for a change, not just describe it.
Whatever you studied
There is a way in from every degree
You do not need to be an engineer or a coder. The scarce skill is business judgement, and that comes from any discipline. Here is what the work can look like, depending on where you are coming from. These are illustrations of the kind of work, not a promise of a role.
Commerce & finance
You take a billing or collections process that quietly leaks money, find exactly where it breaks, and rebuild it with AI doing the repetitive work.
Law & humanities
You turn a slow document or review workflow into one an AI assistant drafts and routes, with a person still owning every judgement.
Arts, media & design
You take a messy customer-communication process end to end, redesign how it actually flows, and show what the change saves.
Science & engineering
You quantify what a process costs before and after, then build the tool that closes the gap and prove it in numbers.
Management & BBA
You map how a function really runs across its handoffs, find the step where time disappears, and rebuild it.
Still studying, or switching
You do not need a finished career behind you. You need to be willing to do the work and learn in the open, next to people who do it for a living.
Week by week
What you learn, and what you produce
You learn by doing, not from a syllabus. But the twelve weeks have a shape. Each fortnight pairs something you learn to do with something you build and keep, returned to you with written feedback.
What you learn
The AI tool landscape: what current tools actually do, where they fail, how to judge one against a task
You produce
An evaluation of three tools against a real business task
What you learn
How a company runs: functions, handoffs, decision points, escalation, where time and money leak
You produce
A mapped process from a real function
What you learn
Building without code: assembling working tools using AI
You produce
A working tool addressing a step you mapped
What you learn
Agentic AI: what can be delegated, what cannot, guardrails and failure modes
You produce
A delegation design with controls
What you learn
Techno-commercial analysis: what a process costs before and after
You produce
A quantified before-and-after model
What you learn
Capstone: one approved internal workflow, redesigned, built, quantified, presented
You produce
Capstone and work record
The other half
That is what you learn. Now, what you get.
The insight and the capability are why it is worth doing. The concrete side, the things the fee commits to in writing, the deliverables you build, and what is yours to keep, has its own page.
Six commitments
Named in the agreement you sign, stated the same way everywhere.
Deliverables you keep
A defined output every fortnight, returned to you with written feedback.
A record at the end
A work record and a Certificate of Completion, described without inflation.
Worth the twelve weeks?
If the insight, the people and the economics are the kind of thing you have been looking for, the next step is a short qualifying test. It costs nothing, and paying never wins a seat.