The intermediate path is where most vibe-coded projects either become real products or die as clever demos. You have a prototype that works on your laptop, a few friends have tried it, and now comes the harder part. Turning that prototype into something strangers will pay for, trust with their data, and return to tomorrow.
Prototypes skip the boring stuff. Authentication, billing, error handling, deployment pipelines, legal compliance. An MVP does not skip those things. An MVP is the smallest version of your product that a real customer can rely on, and getting there requires a specific set of skills in a specific order.
Choose your stack, add auth and billing, deploy to production.
Why the Prototype-to-MVP Jump Trips Up Every Founder
The prototype-to-MVP transition is deceptive because the prototype already looks like a product. It has a UI, it does the thing, people say "wow, you built that with AI" and you start to believe the hard part is over. It is not. The hard part is everything the prototype does not show you. What happens when two users sign up with the same email, when your Stripe webhook fires twice, when someone in Germany signs up and you have no privacy policy. Those are not edge cases, they are Tuesday.
This path walks you through the systems that separate a demo from a product. Each stop is a few hours of focused work, and each one makes your product dramatically more defensible.
The intermediate path is not about learning to code. It is about learning the systems that separate a demo from a product. Authentication, billing, deployment, compliance. Skip ahead and you will backtrack. A founder who deploys before setting up auth will redeploy. A founder who adds billing before planning their data model will refactor. The order matters.
Planning and Preparation
Get your head right before you build the real thing. Founders who rush past planning pay for it in rewrites and wasted credits.
Understand the 70% wall
Before you write a single prompt, understand why AI tools produce impressive results quickly and then seem to stall. Knowing this pattern in advance changes how you budget your time. Most founders allocate two weeks to go from prototype to MVP. Founders who understand the 70% wall allocate six and finish on time.
Pick a stack you can ship on
Your prototype might run on whatever the AI tool defaulted to. That is fine for a demo, but your MVP needs a stack you can hire for, find documentation about, and deploy affordably. Learn the trade-offs behind React, Next.js, and Tailwind so the choice is informed instead of inherited.
Plan before you prompt
The stop most founders skip and the one that saves the most time. Build a structured plan before opening your AI tool. A thirty-minute planning session prevents hours of going in circles with an AI that does not understand your intent.
The build loop
Once you start building, you need a rhythm. Prompt, review, test, repeat. This discipline keeps you out of the most common founder trap, accepting whatever the AI generates without checking whether it actually works.
These four stops feel slow when you are eager to build. Founders who complete them report that the actual building phase goes two to three times faster, because they stop fighting their tools and start directing them.
Building the Core Product
Transform the prototype into the thing your customers will actually use, log into, and pay for.
Build a SaaS dashboard
Your prototype might have a page or two. Your MVP needs a dashboard, the central place where users do the thing they are paying for. This is often the largest single build in the entire MVP process, and getting it right means your users immediately feel like they are using a real product.
Add auth and billing
Nothing makes a prototype feel more like a toy than the lack of login and payment. Authentication and billing are the two features that turn visitors into customers, and the two most likely to have security implications. Follow a structured guide rather than free-styling with AI prompts.
The temptation in Phase 2 is to add more features. Resist it. Your MVP dashboard should do one thing well, your auth should be simple and secure, your billing should handle one plan. Everything else is post-launch scope, and adding it now will delay your launch by weeks.
Getting to Production
Take the product from 'it works on my machine' to 'it works for everyone, legally, with the lights on.'
Deploy your first app
Deployment terrifies founders who have never done it. Modern platforms have made it dramatically simpler than it was even two years ago. You do not need to understand servers, you need to follow a checklist that takes you from local project to live URL in under an hour.
Run the deploy checklist
Getting live is not the same as being production-ready. Environment variables loaded correctly, HTTPS working, error tracking configured, analytics firing. This checklist catches the problems founders discover three days later when a user emails them.
Close the program vs product gap
Even after deployment there is a gap between what you have built (a program) and what users expect (a product). Error handling, loading states, empty states, and the small things that separate software a developer tolerates from software a customer enjoys. Polish is what determines whether your first users come back.
Cover GDPR basics
If even one user from Europe signs up (and they will), you need basic compliance in place. Privacy policies, cookie consent, data deletion. The handful of things that keep you legal without hiring a lawyer. Sophisticated users notice when this is missing, and investors flag it during due diligence.
Launching before completing the deployment checklist is the single most common founder mistake. You get the thrill of a live URL and immediately start sharing it. Then users hit broken environment variables, missing error pages, or unprotected API routes. Your first impression becomes your worst impression. Run the checklist before you share the link. It takes five minutes and saves five weeks of reputation repair.
What Happens After the Intermediate Path
Completing this path puts you ahead of most founders building with AI tools. You have a product that works, is deployed, handles errors gracefully, and respects user privacy. That is an MVP. Not a prototype, not a demo, not a weekend project. The advanced path picks up where this one ends, covering the architecture, security, and scale work that turns a working MVP into something investors will actually fund.
Next on this track
MVP to Investor-Ready
Architecture, compliance, scaling, and knowing when to hire.
The intermediate path is complete when you have a live product, a handful of paying users, and the confidence that your MVP can survive its first real stress test. Everything after that is growth, and growth is a different kind of problem. A better kind.