You've built with AI. Now ship like a professional.
A hands-on course for developers whose AI prototypes fall apart in production. Seventeen modules, one real project: you write the specs the AI reads, drive it well, harden the build, and finish with a live, deployed product and a repeatable method you'll use every day.
$499 at launch · the waiting list locks it at $249
The blueprint for shipping real software with AI.
The full Prompt to Production course covers the entire lifecycle: specs the AI reads, context engineering, a repeatable build method, testing and security gates, and a real deployment with CI. One continuous project carries you from the first prompt to a product in production.
$499 at launch · the waiting list locks $249
What you walk away with
A real product in production
No more toy dashboard clones. Architect, secure, and deploy a live, containerized application built to survive real users and edge-case failures.
An up-to-date framework for AI development
Stop rewriting your code with every new API drop. Master the system design and methodologies that hold up no matter which LLM comes next.
Prompts that make your coding agent sing
Stop guessing and hoping. Build elite system prompts, context files (CLAUDE.md), and test gates that force AI agents to output production-grade code.
Watch the first lesson, free
The complete opening lesson: why AI-written code falls apart as your project grows, and the spec-layer discipline that fixes it. It plays right here, no signup.
The hands-on lab and the Cloach drills for this lesson live in the free module.
More than a set of videos
The lessons and the hands-on labs, plus the people and tools to get your project shipped.
Lessons and hands-on labs
Every module is a lesson paired with a lab. You build the next piece of your own project each time, not a throwaway demo you forget by week two.
Cloach: your course assistant in the terminal
It sits beside you during each lab, knows the exercise you're on, and reviews your prompts so you can see why one works and another doesn't.
A private Discord
A members-only space to work through the material together, share what you're building, and get unstuck without waiting days for an answer.
Q&A Webinars for your questions
When a question keeps coming up in Discord, we run a live session on it, so the course keeps answering the things you actually get stuck on.
Say hello to Cloach (Your Claude Coach)
We didn't just record a bunch of videos and wish you luck; we built custom software for you. Cloach is an interactive CLI assistant that runs locally alongside your project. It knows exactly which lab you're on, tracks your context, and critiques your prompts in real-time.
Lock the waiting-list price: $249
The course launches at $499. Everyone on the waiting list gets it for $249, half off. The list lives inside the free module: claim it, then click "Join the waitlist".
The free alpha: twenty seats
One signup does three things: the free module is yours, your $249 price locks in, and you can apply for one of twenty seats in the alpha.
The alpha is the whole course, free, for a small group that goes through it before the public launch. In return you give honest feedback while you build, and a short testimonial at the end. You apply with a few quick questions, and we take the developers the course genuinely fits.
Lead a team, or want to bring your group up at once? Say so in the application. We're holding seats for developers who can put this to work across a whole team, not only for themselves.
We can only take twenty. If your seat goes to someone else, your waiting-list price still stands: $249 instead of $499.
The path from prompt to production
Five phases, seventeen modules, one continuous build. You begin by talking to the AI and end with a live product people can reach.
Setup & Foundations
environment · spec layer · scaffold
→ a project that boots
Build the First Version
prompting · context · MCP, agents, skills
→ features shipped fast
Research, Plan, Execute
understand · plan · verify
→ a method that scales
Harden the Build
data · tests · security
→ survives real users
Ship & Launch
Docker · CI/CD · deploy · launch
→ live behind your domain
Setup & Foundations
From zero to a project that boots: environment, AI tools, your project chosen and scoped, a scaffold that runs.
Module 1 · Welcome to the AI-Native World
What it means to build with AI as a professional, how the course runs, and your terminal coach: it sits beside Claude Code, knows which lab you're on, and works it through with you.
Module 2 · Your Dev Environment
Install and verify everything, then write your first CLAUDE.md, the briefing document the AI reads.
Module 3 · Choosing Your Project
Pick a real project you'll still want to open at module 17, scoped to a sane first version.
Module 4 · The Spec Layer & a Working Scaffold
Write the documents the AI reads every session, then turn them into a project that boots.
Module 5 · Spec-Driven Development
Make the written spec the source of truth that drives the build. Define what the app must do as a precise, testable contract, then have the AI implement against it and keep the two in lockstep as the project grows.
Building the Project (the Vibe Phase)
Ship features fast by driving the AI well, and feel where pure vibe coding runs out of road.
Module 6 · Prompt Engineering for Developers
Get the code you want, then vibe the essentials of your app onto the scaffold.
Module 7 · Context Engineering
Control everything the model sees so it stops guessing, and ship your second feature with less effort.
Module 8a · Claude Code Setup
Make the tool fit your project: settings, a grown CLAUDE.md, your own reusable commands.
Module 8b · Hooks
Put rules in the runtime around the model so they run whether or not it cooperates.
Module 9 · Minimum Friction
Wire the AI to your files and the tools you use, so you stop leaving the terminal.
Module 10 · Primitives: MCPs, Sub-agents, and Skills
The three building blocks the AI uses to act, delegate, and remember, and how to pick the right one.
Research, Plan, Execute
The methodology that takes over when vibing stops scaling, plus the daily rhythm to run it.
Module 11 · Research, Plan, Execute
Understand the problem first, plan with a real acceptance test, then build in ordered chunks you verify before moving on.
Module 12 · Working with AI: Sessions, Agents, and the Daily Rhythm
How to spend your day with all of it, built around how focus and memory really work.
Hardening the Build
Make it survive: data, tests, code quality, and security, applied with the method from Part 3.
Module 13a · Database & Data Flow
Design your schema with AI assist and map how data moves before wrong assumptions cost you a rebuild.
Module 13b · Testing: Your Safety Net
Integration tests over real user flows, with the test gate wired into your workflow so it isn't optional.
Module 13c · Code Quality & Review
Linting, formatting, AI-assisted code review, and paying down technical debt.
Module 13d · Security
Auth, secrets, and input validation against a real contract, then a security audit of your own project.
Ship It
From your laptop to live with users: deploy, debug, validate, launch.
Module 14 · Deploy to Production
Containerize with Docker, set up CI/CD, and deploy to the cloud behind a real domain with a green pipeline gating every change.
Module 15a · Testing & Debugging
Debug real production issues with AI, and turn every bug you fix into a permanent regression test.
Module 15b · Validation & Security in Production
Catch the silent decisions the AI made, and defend the live project once real attackers show up.
Module 16 · Bootstrap Into Any Field
Ship a feature in a field that's new to you, web for a data person, RAG for a web dev, by getting good enough to judge the AI's output.
Module 17 · Launch Day
Make your project reachable to the people, agents, and crawlers that find it from outside, and ship it.
Is this for you?
You can build, but it breaks in production
You ship features fast, then they fall apart with real users. You'll learn to deploy, secure, and harden your app so it holds up once people are on it.
You're tired of chasing every new release
You want to stay ahead without relearning the tool every few months. You'll get a method that holds as the models and tools keep changing.
Your AI project is stuck in a notebook
You build RAG apps and agents that never leave your machine. You'll turn one into a deployed, secured product with your name on it.
Not for you if
- You want a no-code tool. You write real code here.
- You'd rather watch than build. The labs are the point.
- You want a one-off demo, not a method you keep using after the course.
Who's teaching this
Nir Diamant
Open-source AI guides for developers, 83K+ GitHub stars and a 40,000+ AI-dev newsletter.
Roi Halamish
Owner of several software companies, and a practitioner and thought leader applying AI development techniques.