What actually is an MVP?
A practical foundation for minimum viable products, assumptions and learning.
The MVP Founders Programme is twelve weeks of instructor-led product management and AI-assisted software development. Every session has clear objectives, a worked example, a Claude Studio exercise and a workshop, all applied to the product you bring.
Map the problem. Validate the idea. Plan the product. Assemble with AI. Ignite the business. Weeks 1–6 take your product along the whole route once; weeks 7–12 run it again at scale, with Claude inside your product.
Understand the problem
Prove the opportunity
Define the MVP
Build, show and grade
Launch and grow
Tuesday and Thursday, 18:00–20:30 (UK). Each session moves through the same rhythm:
Products start with problems · Who it is for and why they would switch
From evidence to a testable bet · Vision, strategy and focus
Designing the experience · How software products work
From decisions to a build-ready backlog · Briefing Claude, your engineering partner
The build loop · Quality you can trust
Launch to your first users · Learn, decide and plan the next loop
Evidence at scale: retention and behaviour · Research at volume, and the AI opportunity
Business model and pricing · Shaping the AI feature bet
Designing AI experiences · From product to platform
Your first Claude-powered feature · Evals, cost and reliability
Security, privacy and safety at scale · Ship continuously and scale on evidence
Go to market · The business case and demo day
See pricing and join the waitlist →
© 2026 MVP Studios Ltd. MVPAI™ and the MVP Founders Programme materials are original works of MVP Studios Ltd. All rights reserved. No copying, redistribution or commercial use without written permission. Course terms
Structured product knowledge: theory, framework, real-world application and reflection.
A practical foundation for minimum viable products, assumptions and learning.
From problem framing and strategy to lifecycle decisions.
A practical introduction to Scrum and iterative product delivery.
Use empathy, framing, ideation and prototyping to explore better solutions.
Design useful AI products around evidence, evaluation and human needs.