Your agents already write code. You just cannot trust it yet.
The agent writes code in minutes, and you still read every diff twice, hunting for the place it got something almost right. We teach you to build with agents the way we ship in production: with steering, verification and a trace you can trust, not prompt-and-pray.
Instead of a talk about trends we work on your real code: how to make the agent get it right the first time and get it right repeatably, so you stop cleaning up after it after hours. Led by engineers whose agent-built systems run in production under load, not career trainers.
- You talk to an engineer, not a salesperson.
- 30 minutes, no sales presentation.
- No prep or homework on your side.
1:1 session participants
What you leave with.
Kuba Koziej CEO & co-founder of MoreGrowth, board member at Natu.Care
I went from barely shipping a frontend to building full applications with a backend and a database, and deploying them safely instead of hoping they would hold. We worked through the parts I kept tripping on: Docker, the coding agents and tools, and when it is worth reaching for skills, MCPs and connectors. It stayed practical the whole way, on what I actually wanted to build.
Hlib Utkin
Public administration
A large stream of documents passes my desk every week. I now review, draft and prepare them with Claude in a fraction of the time, and research that used to eat an afternoon takes minutes. It is wired into the services I already work in, so the documents reach me instead of me hunting for them.
Ivan Chepurin Senior Software Engineer, Immutable
I came in using coding agents ad hoc and left orchestrating them: loops, an agent kanban, a full development cycle that ships. What stayed with me is running context and cost on purpose, and building my own harnesses instead of waiting for a tool to ship one. It changed how I work day to day.
Oleksandr Usyk Co-founder & Art director, jakotako
I run a design studio, not an engineering team, and I still left with something working. We built an agent loop that pulls in leads and keeps an eye on the competition, and I put my own site together with Claude. It was hands-on, on my real work, not a talk about AI.
In short
- Price
- Quoted after a callpaid; it depends on format and scope, we give you a real figure after one call about your repo
- Format
- 1:1 or a small cohort, onlineon your real repo, not on exercises
- Who teaches
- Engineers building with agents in productionthe program comes from our builds under load
- For whom
- A dev, founder or solo buildernot for non-technical teams (see AI training)
The agent built it in an hour. How long do you then spend checking after it?
Agents write code faster than you can read it. Count the hours a week that go into re-reviewing and cleaning up after the agent: that is the price of no steering and no verification. You will not recover all of it, some review always stays human; the point is to stop paying for it twice. The root cause is one thing: the agent optimises for what looks plausible, not for what is proven, because nothing forces it to. Everything else follows: it drifts off spec, prose specs rot, unit tests pass while the product breaks, and the docs go stale the moment the code moves.
It is the same method our own builds run on, in production, under load. See case studies →
AI-Native Harness
What changes once you take the wheel.
Three things that turn 'the agent kind of worked' into 'I can trust it': control, verification, and a method that stays with you.
Control, not hope
The agent does the right thing inside the bounds you set, instead of prompt-and-pray. The result is repeatable, not a roll of the dice.
- A repeatable result, not a lottery
- Clear bounds on what the agent may do
- A human approves where it matters
Verification, not trust
Instead of believing the agent got it right, you check it. The product's behaviour is proven, not assumed, and a green run actually means it works.
- Behaviour proven, not guessed
- A green run means it works
- The only-probable answer gets caught
A method that stays with you
You leave with your own written method, not notes. Repeatable on every next project, and the same method onboards a team once you grow.
- Your method, written down and repeatable
- Long projects that do not drift
- Scales to a team once you grow
What you will learn.
Each module pairs working with agents with the discipline that makes the output trustworthy. We fit the scope to your stack and your goal.
Theory · groundwork
How agents really work and where they fail, before we touch your repo.
01GroundworkHow agents really work, and where they fail
Where the errors and the only-probable answer come from, before we touch your code.
- 02Trust
From 'the agent kind of worked' to 'you can trust it'
Why taking the agent's word for it is not enough, and how to turn trust into something you can check.
Practice · on your repo
You drill on your own code and finish with a pilot, not a toy example.
03ControlAn agent that gets it right the first time
How to keep the agent inside bounds so the output is repeatable and production-ready, not something you clean up after.
- 04Verification
Requirements that verify themselves
How to stop requirements rotting in the repo and make them keep proving the code still does what it should.
- 05Discipline
A long project that does not drift
How to hold order, context and documentation over a long build so the project does not fall apart after a week.
- 06Pilot · Scale
A pilot, and a method that stays
How to close the learning with a real pilot, and how the same method onboards a team once you grow.
Two kinds of builder, one method.
The depth depends on who is in the room, but you leave with a method that stays on your repo. A whole team? That is the cohort, the same course on a shared codebase.
A technical founder
A founder who codes and ships product themselves.
- A repeatable way to build with agents
- An agent that gets it right the first time
- What to automate first, what to keep human
- You leave with a working setup, not notes
A solo builder or small team
An indie hacker or a small team moving into agent work.
- Agent work that holds under real load, not demos
- Control and verification you can trust
- Context and cost kept on a budget
- A method that grows with you
Formats and price
1:1 or a team cohort, on your repo.
The same method, online: one-on-one, a small group, or a team cohort, always worked on your real codebase. The final quote depends on scope, the stack and how many people take part.
1:1 intensive
A founder, engineer or solo builder who keeps building after the course.
One-on-one on your repo: we stand up the method on your real codebase and the way of working that holds after we leave.
Quoted
after a call · net
Team cohort
A dev team moving into agent work
A cohort on a shared codebase: the same method and conventions, so the whole team leaves working the same way and closes with a pilot.
Quoted
after a call · net
You pay once; the method and what you walk out with stay yours. We set the rate to scope, the number of participants and your stack after one call about your repo and goal, and if the course is not for you, we will say so before any quote.
Who it is for, and who it is not.
This is about readiness, not skill level. If the second column describes you, another path usually fits better, and we will say so on the call, before you ever see a quote. We would rather send you where it actually helps than sell a course that will not change how you work.
Ready if
- You build software and want a repeatable agent harness
- You have a real repo to work on, not just curiosity
- You want output you can trust, with specs, tests and a trace
- You will keep building after the course, not hand it off
Probably not, if
- You want it built for you: start with the free scan and our builds
- You need AI literacy for a non-technical team: see AI training
- You want a no-code promise or a certificate for the wall
- You expect production hardening, ownership and SLA from a course
Or we build it with you
Rather have it built and run in production?
The course teaches the method. Production hardening, ownership and maintenance stay a paid build. If you would rather not do it yourself, start with the free process scan, and we will tell you straight what is worth building, and whether it is worth building at all.
From a call to a working harness.
The course starts with one call about your repo, your stack and your goal. We run the rest in a clear order.
- 01A call about your repo, stack and goal: we set the format and scope.
- 02You get a quote and a plan fitted to your codebase.
- 03Working sessions on your real repo, online, building the harness.
- 04You keep the harness, the templates, the way of working and a pilot done the new way on your repo.
Tell us your repo and goal, and we will send a plan and a quote.
- 30 minutes with the engineer who would build it, not a salesperson.
- A review of the processes that cost you the most time and money.
- A written summary: what to automate, in what order, with cost ranges.
No sales deck and no obligations. If automation doesn't make sense, we'll write that too.
Paid course · quoted per scope · led by engineers with systems in production
Questions about the course
Why pay for a course when I could figure this out myself?
You could, and some people will. The question is how many months, and how many commits you shipped to production without trusting them, it takes. You are paying for the shortcut: a method that has already been through our builds under load, set up on your repo from day one, not for knowledge you can find in the docs.I already tried agents and rewrote the code anyway. How is this different?
That is exactly what the course is for. We do not show you better prompts; we show you a way of working where the agent stays inside bounds you set and its output gets checked before you trust it. The starting point is the very code that burned you.Won't I learn something that is stale in six months?
We teach the method, not one tool's configuration. Models and plugins change; the way you set bounds for an agent and verify the result stays. We show it on your repo and you close with a pilot, so on Monday you go back to code where it already works, not to a blank page.Why don't you list a price?
Because we will not make one up. The rate depends on the format (1:1 or cohort), your stack and the scope, so we give you a real figure after one call about your repo and goal. On that same call we work out the hours a week you lose today cleaning up after the agent, so you decide on numbers, not a promise. When it is cheaper and more sensible to start with the free process scan, we say so plainly.Which stack and repo do we work on?
Yours. We work on your real codebase and stack, so the harness fits what you actually ship. If you do not have a repo yet, we start one together in the first session.Claude, or other models?
We work most on Claude and Claude Code, the way we build ourselves, but we also teach in OpenAI's tools and others if that is what you use. We say plainly where another model or tool fits better, with no false claim that one is always best.Is it a team cohort or 1:1?
Both. A team cohort, a small group, or 1:1 for a founder, on a shared codebase. We set the format with you before the quote.What do you need to start?
A repo and a goal. We set up the environment and tooling as part of the course, tuned to your stack. You do not need anything special before we begin.What do you keep afterwards?
The method on your repo, the way of working and a pilot project done with it. It stays with you, not on our slides.