AI-native operator training
Learn to direct AI agents to build real software, systems, workflows, and business assets — with the specs, taste, judgment, testing, and launch discipline that separate operators from passive AI users.
The rules that keep agents aligned — written down, not prompted ad hoc.
Proof, not hype
Not screenshots of a demo — the actual artifacts the method produces. Each one answers a single question: what does this prove?
operating-doc
Agents stay aligned across sessions because the rules are written down.
spec
The build is judged against a definition, not a vibe.
qa
What demos skip — the checks that catch broken edges before users do.
events
The funnel is instrumented from day one, not bolted on later.
deploy
It's a deployed system with a rollback mindset, not a localhost demo.
The problem
It can't tell you how the thing should work, how it should feel, whether the architecture is sane, when it's safe to ship, or whether any of it matters commercially. That judgment is the job. That judgment is what's scarce.
The reframe
Passive AI users collect outputs. Operators turn judgment into systems. The difference isn't a better prompt — it's specs, taste, review, testing, and launch discipline applied to a workforce of agents.
Stop using AI like a chatbot. Start operating it like a workforce.
What you can build
Real systems, not toy demos — the kind that used to require a team.
The method
Spec → Orchestrate → Review → Ship → Grow. The discipline that turns agent output into systems you can trust, deploy, and improve.
Decide what should exist and write it down with acceptance criteria.
Direct agents through architecture and build, in reviewable slices.
Read the work, catch drift, and redirect before it compounds.
Test in the browser, deploy, and instrument what matters.
Run the first distribution loop and iterate on real signal.
Proof in the wild
The brand isn't built on one project. New builds across software, tools, and workflows are added here as worked case studies.
Marketing site + funnel
The site you're reading was specced, designed, built, instrumented, and deployed by an operator directing AI agents — using the exact loop the course teaches.
What this proves
The method produces a real, fast, instrumented product — not a demo.
Lead generation (DE)
A real German lead-gen platform built with agents: a multi-step funnel engine, lead scoring and attribution, an admin dashboard, partner delivery, transactional email, tests, CI, and deployment.
What this proves
Agents can build the parts demos skip: auth, data, admin, email, QA, deploy.
Built on camera
New builds across software, internal tools, research, and workflow automation are being recorded and added here as worked case studies.
What this proves
The loop generalizes far beyond any one project.
The course
Ten modules that take you from a commercial idea to a deployed, instrumented first slice — running the Operator Loop on your own project.
Why AI changes the work stack, what agents can and cannot do, and the Operator Loop you'll run on a real project.
Choose something worth building. Score ideas on revenue, leverage, and feasibility — and avoid fantasy apps.
Why operating docs beat one-off prompts. Write the AGENTS.md system that keeps agents aligned across sessions.
A PRD without the bloat: user journeys, acceptance criteria, data requirements, edge cases, and what to defer.
Direct UX without accepting ugly defaults. Write a design brief agents can build from, mobile-first.
Frontend, backend, data, auth, email, analytics. Read architecture options, choose a stack, and know when to escalate.
Break a build into slices, issue tasks, read diffs, prevent drift, and recover from bad agent work.
What you can review without pretending to be a senior engineer — and the checklists that catch what agents miss.
Ship it: Vercel, env vars, domains, transactional email, analytics events, and a rollback mindset.
Get the first users. Landing pages, lead magnets, content-led distribution, analytics review, and iteration.
Pricing
The course is scalable education. Hands-on review and audits live in higher tiers, priced honestly. No fake scarcity.
Founding Edition · one-time
Build Real Software With AI Agents
The complete recorded course plus every template and teardown. Everything you need to run the Operator Loop on a real project.
Recorded + templates. No personal debugging or done-for-you work.
Founding · application
Core, with eyes on your project
Everything in Core plus bounded review of your operating docs, spec, and milestone plan, group clinics, and Q&A during the launch window.
Capacity-capped on review workload. No unlimited debugging.
Application
A real project, audited and de-risked
For founders, agencies, and businesses with a live project. Deep project audit, architecture/spec review, agent-readiness review, and a launch plan.
Explicit scope. No hidden retainer, no unlimited Slack.
Custom
Train your team to operate agents
Workshops, internal playbooks, and agent-workflow audits for agencies, product teams, and operator-led companies.
Scoped per engagement.
Founding price held for the first cohort only. 14-day refund if you do the first two modules and it isn't for you.
Fit
FAQ
Start here
The operating-doc, spec, design-brief, and QA templates real operators use to direct agents. Then decide if the course is for you.