Fixes that break other things
Founders described losing whole days to a tool that repaired one screen and quietly broke another. Then insisted, confidently, that it hadn't.
We sat down with non-technical founders who had built real products with AI tools: app builders, chat assistants, the lot. Every one of them had something to demo within days. Every one of them then spent far too much time and credits trying to turn that demo into something people could actually rely on and use. This course is built out of what they hit along their journey.
Founders described losing whole days to a tool that repaired one screen and quietly broke another. Then insisted, confidently, that it hadn't.
Output can't be taken on trust, so everything gets verified manually. The verification burden eats up exactly the speed that made the tool worth using.
Decisions made last week are forgotten and are re-discussed this week. A human teammate would have absorbed it once; the tool needs telling every time.
Features get added because they're easy, not because the product needs them. Onboarding grows, the thing gets complicated, and the actual v1 never arrives.
Every founder finishes with their own product live in production. Here's what "usable v1" means on this course. It's a checklist, and we review your product against it.
See it done, do it on your own build, and get unstuck by engineers in the same week. We front-load the foundations that make the rest go fast, and pace it for founders who are fitting this around everything else.
Taught live, not left in a video library, worked through on a real product in front of you, so you have seen it done before you do it on your own.
You bring your actual broken thing. Technical questions and product questions both welcome. The ones that stall founders are usually a mix of the two anyway. This is the part you can't get from a tutorial.
The founders we spoke to went straight for features and paid for it: silent breakage, hand-checking every release. We start the other way round: a behaviour model, a data model you own, a design system, tests, monitoring. That's what makes an agent fast and your product safe to change. Foundations first is the fastest option, not the careful one.
You've got a business to run or a job to pay for it. The pacing assumes evenings and weekends, with a two-week break over Christmas. Full-timers can go faster; the sequence is the same.
Works at the intersection of AI, startups and accelerator programs, and runs Generation AI. Has watched a lot of founders build a lot of first versions, which is a useful thing to have in the room.
Ten-plus years building software, including safety-critical systems where being approximately right isn't good enough. Spends his time on how founders actually get real work out of coding agents, and where those agents quietly fail.
Twelve workshops across six months, plus weekly technical office hours. Foundations first, then architecture, then the loop that turns your design into shipped, deployed software.
How software works end to end, your environment and version control, then the two things every build rests on: a behaviour model of your product and a design system it is built against. The groundwork that makes everything after it faster.
Workshops 1–3The decisions that are expensive to get wrong: the language of your domain, its boundaries, your tech stack, your data, the rules it can't break, and the contracts between the pieces.
Workshops 4–6Your architecture becomes epics and stories. You build one story by hand and have it reviewed by AI until nothing serious is left. Then you learn to loop the rest.
Workshops 7–8A whole epic looped, QA'd and deployed. Then the safety net that lets you keep changing it: regression tests, monitoring, logging, and agents that drive your app like a user would.
Workshop 9Your product stops living on your machine and goes somewhere anyone can reach it. A real deploy pipeline where a push ships itself, a staging environment to catch problems before your users do, and your own domain out front.
Workshop 10How to keep a product alive after launch: iterate on real usage without bloating it, maintain it (security, customer data, upgrades, and what to do when something breaks), and think about scale as traffic, data and load grow past what you first built for.
Workshops 11–12There's more than one way to get a first version built, and some of them are genuinely good. What makes this one different is what's in your hands at the end: a product that's live, and a written definition of how it works that keeps paying off long after the build.
They're brilliant at getting something on screen fast, and most founders here arrive with one already. The pattern is the same for everyone: the first two weeks are astonishing, and then the app gets big enough that each new feature costs more than the last. This course is about what you do at that point. Give the tool a real definition of your product to build against and the ceiling moves: the complexity lives in writing, not in how much the model can hold in its head at once.
Absolutely, once it's earning. An agency or freelancer will quote $20k–50k for an MVP, and early on, when you're still experimenting and hunting for product-market fit, every change after that is another quote and a wait. Most of those changes get thrown away. That's an expensive way to learn what your customers want.
Prompting gets you a long way, and you'll be doing plenty of it here. The lift comes from what you give the agent to work with. Every workshop puts another layer of your product into writing: behaviour, boundaries, data, the rules it can't break. Agents get dramatically better when they're building against a definition instead of guessing at one. That's the whole skill.
Two things, and only one of them is code. The product is the obvious one: live, on your URL, maintainable. The other is your spec: a written definition of how your product behaves, what its data means, and the rules it can't break. It's the most durable asset you'll own: what makes an agent productive instead of confidently wrong, what you hand a developer, co-founder or investor without a three-hour explanation, and what survives when the model changes, the framework changes, or you rebuild the whole thing in two years. Code gets replaced. The thinking doesn't.
Seats are limited by how many builders we can genuinely support in office hours. Start with a call: we'll look at what you're building and tell you straight whether AI engineering is the right way to get it built.
for the MVP, then a fresh quote and a wait for every change after it.
plus super and management time, before they've shipped anything.
of everything you ever build — if you can find the right one.
On this course you build it yourself, with real engineers on call every week.
The six months include
Not sure AI engineering is the right approach?
That's what the call is for. We'll look at where your product is and what you've built so far, and give you a straight answer on whether this way of building fits — even if that answer is to stay in your app builder.
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That's who the course is built for. Week 1 starts at what a frontend, a backend and a database even are. What you do need is willingness: to open an editor, to be a beginner for a few weeks, and to put in the hours between sessions. If you have that, the technical part is learnable. We've seen founders with no background at all get further than they expected.
Around 8–10 hours a week: one or two live sessions plus the work on your own product in between. It's paced for people running a business or holding down a job. The founders who stall aren't the ones who find it too hard. They're the ones who couldn't protect the time.
There's a two-week break from 21 December to 3 January, and we resume on Monday the 4th. The schedule is built so you go into the break at a natural pause point, not mid-build.
Yes. The whole course is structured around your product, so you need something real to build: an idea you've thought hard about, or a prototype you've already made. What you don't need is a validated business or paying customers. Scoping it down to a shippable v1 is part of the course; deciding what to build isn't.
No. It's the best possible starting position, and it's what most people arrive with. In Week 4 you bring it across. Be clear on what that means though: the old build becomes your reference, not your foundation. You'll be rebuilding it properly, which is faster than it sounds because you already know exactly what you want.
An AI coding subscription and a handful of services, most with free tiers that cover a product at this stage. Budget somewhere around $50–150 a month depending on how hard you push it.
Tell us any time up to the end of Month 01 and we'll part ways — no forms, no negotiation. By then you've had three workshops and four office hours, which is enough to know whether this is how you want to build.