A five-day live course that teaches school leavers to build with AI. No coding required. They arrive with a laptop and leave with a team of AI agents that researches, writes, and works on their behalf. They built it themselves. They keep it.
15 places per cohort. When it fills, it's gone. £50 deposit holds the spot.
£799 early bird before 1 May. £1,000 thereafter.
Most teenagers use AI the way people use a calculator. They type something in and read what comes out. That is consumption. It is the skill equivalent of knowing how to Google.
Building with AI is something else entirely. It means creating agents that research on your behalf, write in your voice, analyse data while you sleep, and work as a coordinated team. Among professional software developers, only 31% have even tried this. Among school leavers, the number is effectively zero.
Your child is about to enter a world that assumes this capability. This summer is the window to give them that foundation before the year it matters.
Your child walks into their first university seminar, or their first week at a new job. The person sitting next to them has an AI research assistant that reads 50 papers overnight, a writing agent that produces structured first drafts, and an analysis tool that does in minutes what used to take a weekend. Your child has none of this. The gap is not theoretical. It has a date, and it is closer than you think.
Schools aren't built to move this fast. No curriculum cycle is. The syllabus written three years ago cannot teach what matters today, and by the time it is rewritten, it will already be behind. This summer is the right moment — before your child needs these skills in earnest.
By Friday, every student has a personal AI team on their laptop: agents they designed and configured themselves, each with a specific role. They keep everything they build.
Day 1
Set up their environment, interact with Claude, and understand what is really happening under the surface. Tokens, context windows, why models sometimes get things wrong. By the end of the day, they have run their first agent and watched it do something useful. That moment changes how they see the technology.
Day 2
Frame problems, structure reasoning, build a research workflow. How to get AI to show its working, check its own output, and iterate toward something genuinely good. This is the day students stop treating AI as a search engine and start treating it as a thinking partner.
Day 3
Define their first agent: give it a role, a set of instructions, a personality, a job. Then a second. Then a third. One researches. One writes. One reviews and challenges. By the end of the day, they have a working team of at least three agents, and they can feel the difference between talking to a chatbot and directing a team that works for them.
Day 4
Students pick the project that fits their future:
Entrepreneur track
Build a working prototype of an AI-powered business tool. A market research agent that scans competitors, a content agent that writes in their brand voice, a customer outreach agent that drafts personalised messages. A real startup toolkit, not a classroom exercise.
Student track
Build a personal research and study assistant tailored to their degree subject. A source-analysis agent that reads academic papers, an essay-planning agent that structures arguments, a revision coach that tests their understanding. They arrive at university with a system their coursemates will not have for months, if ever.
Day 5
Every student presents their AI team to the cohort: what each agent does, how they built it, what they learned. They can explain it to a parent, an admissions tutor, or a future employer. It is not a participation certificate. It is a working project on their laptop that they built from scratch, can demonstrate, and can keep building.
There is a particular moment in a teenager's relationship with their parents where they stop asking for help and start solving things themselves. This course is designed to move that moment forward.
This course is for the student heading to study History, Law, Medicine, Economics, or Business who knows AI matters but has no idea where to start. The one who will spend three years at university and then walk into a workplace that treats AI fluency as a baseline.
Toby has spent 20 years building and launching products inside large organisations. Before that, he spent years developing personal knowledge management systems and coaching hundreds of product owners online — focused on process, automation, and how to make complex tools actually work for real people. That thread of obsessive systems-thinking is what led, eventually, to AI.
He now runs Vester Energy, an AI-powered energy advisory business he built from scratch using the same tools and methods students will learn on this course. At the centre of that business is a personal AI operating system: a set of specialist agents that do research, write reports, analyse data, and run his workflow. He built it himself. He uses it every day.
His thesis — the one this course is built on — is that learning by doing is the only way to master these tools. Reading about AI produces familiarity. Using it, building with it, and finishing something real is what produces capability. That is what the week is for.
The price covers everything: five days of live instruction and all course materials. Claude AI is free to use — no subscriptions, no software licences, no hidden costs. Just bring a laptop.
The self-taught path to a comparable level of AI fluency takes 100 to 200 hours spread across five months, assuming the student knows where to start. This course compresses it into 10 guided hours with a practitioner who has already done the work. For £799, your child walks into university or work this autumn with a capability that puts them ahead of the vast majority of their peers.
Early bird pricing closes on 1 May. That is 26 days from now. After that, the price is £1,000.
Places are limited to 15 per cohort. When a cohort fills, it fills.
£50 deposit secures the place. Full details below.
This is your preferred week. We'll confirm your place once dates are locked.
A £50 deposit secures your child's place in the next available cohort. That is the only commitment today.
Each cohort is no more than 15 students. This is not a product that replenishes. When the places are gone, they are gone. The £50 holds your child's place. That is all it does.
Here is how the deposit works:
You will be taken to a secure Stripe checkout. £50 deposit only — no further charge until dates are confirmed.
Not ready yet? Leave your email and we will let you know as soon as dates are confirmed.
No. The course assumes zero coding experience. Students write instructions in plain English. The goal is AI fluency, not software engineering.
Especially. AI is changing how research, writing, and analysis work in every field. A law student or medical student who can build AI agents for their workflow has a genuine advantage. The course is designed for exactly this student.
Students join a video call each day, like a small seminar. Maximum 15 per cohort. The instructor leads, students build on their own laptop. It is interactive, not a lecture.
Claude is an AI platform made by Anthropic, one of the leading AI research companies. It is the tool students use to build their agents. Claude is free to use — there is nothing to set up or pay for separately.
Students leave with working projects on their machine and all course materials. Claude is free to use — they have everything they need to keep building. What they build next is up to them.
No certificate. What they leave with is better: a working AI project on their laptop that they built themselves, can demonstrate to anyone, and can keep developing. That is a stronger proof of skill than any certificate.
Full refund, no questions asked.
Free tutorials teach prompting, which is the equivalent of learning to type a Google search. This course teaches students to build AI agents, connect them into a working team, and use them for real tasks. The self-taught path takes months. This course compresses it into one week with a practitioner who has already done the work.