Stop building AI wrappers.
Master Production AI in 4 Weeks.
A 4-week, hands-on sprint for Technical PMs and Software Engineers. Learn enterprise AI patterns, build your custom application, and deploy to production.
Next cohort starts May 2026. Strictly limited to 20 builders.
Only 7 spots remainingTrusted by Technical Leaders
Built for Technical Professionals, Not Absolute Beginners.
You already understand how web apps work. You don't need another "Hello World" tutorial. You need a proven, production-grade architecture to build meaningful AI products. We skip the basics and dive straight into advanced AI engineering.
Pre-requisite
You are a Technical PM, Software Engineer, or technical founder.
The Goal
You want to lead AI initiatives and build complex, valuable AI applications.
The Method
We focus entirely on AI orchestration, state management, and deploying real infrastructure using a modern stack (Next.js, Vercel AI SDK, Supabase pgvector).
Your Unfair Advantage: The Starter Kit
We believe you should spend your time building AI logic, not wrestling with boilerplate. When you enroll, you get immediate, lifetime access to our proprietary codebase—the exact production-grade foundation I use to ship apps every 30 days.
Next.js 14 App Router
A pre-configured, production-ready frontend and backend.
Vercel AI SDK
Integrated for best-in-class streaming and AI state management.
Supabase Integration
Pre-built helpers for seamless connection to your Postgres database.
pgvector Ready
Your database is already enabled with vector extensions for immediate RAG development.
User Authentication
Secure, pre-built login, signup, and session management using Supabase Auth.
Shadcn/UI Components
A full suite of beautiful, accessible UI components ready to be used.
Payments Ready
Pre-configured Dodo Payments / LemonSqueezy integration to monetize your app.
Email Integration
Ready-to-use Resend integration for transactional emails.
Your Path from Engineer to AI Engineer
The program is a rigorous but manageable sprint. Expect to commit 1–2 hours on weekdays and 3–4 hours on weekends.
The Async Pre-Flight
Consume the AI Engineering Vault videos and get our proprietary Starter Kit running on your machine.
Architecture & UI Scaffolding
Lock in your project scope based on one of our blueprints. Configure your Supabase database and build the React UI shell for your dashboard.
The Core AI Engine
The deep technical week. We wire up the Vercel AI SDK, configure your RAG embeddings, or set up your LLM tool-calling schemas.
UX & State Management
This is where the magic happens. We connect the AI logic to the frontend, building human-in-the-loop review panels, streaming markdown, and interactive UI states.
Polish & Production
Handle edge cases, deploy to Vercel, and present your live, full-stack application at our official Demo Day.
Bring Your Own Project. We Provide the Enterprise Architecture.
To ensure your project is unique and valuable, you bring the idea. To ensure you actually launch, we map your idea to one of our three proven, full-stack architectural patterns.
The "Human-in-the-Loop" (HITL) Data Engine
The Pattern: Forcing LLMs to output strict, validated JSON from unstructured data, combined with a UI that allows for human review and approval.
Example Use Cases
- •An automated Invoice Digitizer that flags low-confidence extractions for review
- •A User Interview Synthesizer that categorizes feedback but lets you edit the tags
- •A Resume Parser that scores candidates but allows HR to approve the final shortlist
The "Context-Aware Workspace" (RAG-Powered Search)
The Pattern: Storing vector embeddings natively in Supabase (pgvector) to build hallucination-free AI that streams answers and provides clickable, verifiable citations.
Example Use Cases
- •A private codebase copilot that cites the exact file and line number for its suggestions
- •An internal PRD engine that lets you ask questions and see the original source document
- •A legal-tech app that analyzes contracts and highlights the specific clauses it references
The "Autonomous Multi-Step Agent" (Agentic Workflows)
The Pattern: Giving the LLM "hands" to execute multiple tools in a sequence, paired with a UI that streams its multi-step "thoughts" to the user in real-time.
Example Use Cases
- •A text-to-SQL analytics bot that shows its query plan before executing
- •A real-time competitor intelligence agent that logs its search, scrape, and synthesis steps
- •An automated bug reproduction agent that documents its attempts to replicate a user-submitted issue
More Than a Program—It's Your Inner Circle
The sprint ends in 4 weeks, but your journey doesn't. You're being accepted into a private, vetted community of ambitious builders who are shaping the future of AI. Our private Discord is the heart of it all.
Connect with Vetted Peers
Network with high-caliber PMs and SWEs. Find co-founders, get feedback, and solve problems with people who speak your language.
The "Unstuck" Machine
Tap into the collective brainpower of the community and get your advanced architectural questions answered in hours, not days.
The Opportunity Engine
Gain access to the exclusive #gigs-and-opportunities channel for freelance projects, full-time AI roles, and collaboration requests.
Alumni-Only Events
Join our monthly "AI Teardowns," advanced workshops, and Q&A sessions with guest experts to stay at the absolute cutting edge.
From the Trenches, Not the Sidelines
I'm the founder of MVP Launchpad OS. For 25 years, I've been a software engineer, architect, and tech lead. I've built enterprise systems for millions of users, navigated multiple tech bubbles, and lived through the entire evolution from monoliths to microservices to today's AI-native world.
I'm still a full-time engineering leader at a major firm, which is why I run this program pseudonymously. But it means that what you learn here isn't theory from a retired consultant; it's the exact, battle-tested stack and architectural patterns I use every single day to ship production AI products.
I created this incubator for one reason: I see brilliant technical PMs and engineers getting paralyzed by AI hype and bloated frameworks. My mission is to cut through the noise and give you the two things you actually need: a production-grade codebase, and the architectural mentorship to build something meaningful with it. In our sessions, I'm not a lecturer; I'm your fractional CTO.
Proof of Work: Recent Ships
From grapine.ai — I don't just teach this architecture; I live in it. Here are four recent AI products and open-source tools I've shipped using the exact Next.js, Vercel AI SDK, and Supabase stack you will master in the incubator.
What it does: A role-based prompt engineering simulator that turns AI prompting into a measurable, job-ready skill for enterprise teams.
The Architecture: Built using an advanced AI-on-AI evaluation pipeline. It utilizes structured JSON outputs to dynamically score user prompts against a strict grading rubric, managing complex, multi-turn conversational state in Postgres.
What it does: An autonomous competitive intelligence engine that tracks market movements, feature releases, and rival positioning in real-time.
The Architecture: A textbook implementation of the Multi-Step Autonomous Agent blueprint. It uses LLM Function Calling and tool-use schemas to orchestrate live web scraping, data synthesis, and scheduled cron jobs.
What it does: A smart context-compression library for agentic workflows. It drastically reduces token costs by removing stale tool outputs and resolved reasoning before the next LLM call.
The Architecture: Deep LLM memory management. Demonstrates how to handle context windows and token reduction at the edge—a critical skill for scaling production AI without bankrupting your API budget.
Agent-Glass
What it does: A Man-in-the-Middle (MITM) observability proxy for LLMs on your local machine. Available soon on PyPI and npm.
The Architecture: Intercepts network payloads to log Time-To-First-Token (TTFT), inspect hidden system prompts (from Claude/Codex), and debug agentic requests in real-time.
Open-sourced to the community. Proves my commitment to deep, system-level engineering rigor—the exact rigor you get inside the MVP OS Starter Kit.
Choose Your Launch Track
Only 7 spots remaining — Apply nowThe AI Engineering Sprint
Best for Technical PMs and SWEs ready for a guided, hands-on path into AI.
- The MVP OS Starter Kit Codebase
- Lifetime Access to the AI Video Vault
- Map your idea to 1 of 3 Blueprints
- 4 Live Weekend Mentorship Calls (1 structured session each week)
- 4 Weekday "Office Hours" for optional, live debugging
- 24/7 Discord Access with Community & Mentor Support
- Lifetime Inner Circle Community Access
The Fractional CTO Incubator
Best for founders or senior leads who need 1:1 architectural guidance.
- Everything in the Engineering Sprint, PLUS:
- 4 Live Weekend Mentorship Calls (1 structured session each week)
- 4 Weekday "Office Hours" for optional, live debugging
- 1-on-1 Architecture mapping call before Week 1
- Direct, asynchronous code reviews from me
- Priority 1:1 Discord Channel
- Build a highly custom edge-case architecture
Frequently Asked Questions
Ready to ship?
Have a question or need guidance choosing the right track? We're here to help.