How to Build a SaaS MVP in 3 Days with Next.js (Not 3 Weeks)
A step-by-step guide to shipping production-ready SaaS products in 72 hours using Next.js boilerplate and AI-assisted development. Real timeline, real code, real results.
Wojtas MaciejThree days. That's all it takes to go from zero to a production-ready SaaS MVP. I know because I've done it 12 times. Not prototypes or tutorial projects—real, deployed applications with paying customers. Auth, payments, database, everything.
This isn't theory. It's the exact workflow I use to ship SaaS products. The same process I'm about to share worked for me every single time. Here's the complete breakdown.
⚡ Reality Check
This guide assumes you're a developer with Next.js experience. If you're new to web development, expect 1-2 weeks instead. Still 10x faster than building from scratch.
Day 1: Foundation (4-6 hours)
Hour 1-2: Setup & Configuration
Start with a production-grade boilerplate. Don't build authentication from scratch. Don't configure MongoDB manually. Don't set up Stripe webhooks for the hundredth time.
What you get immediately:
- Next.js 14 with App Router, TypeScript, Tailwind CSS
- NextAuth authentication (Google, GitHub, email/password)
- Stripe payments with webhook handling
- MongoDB with Mongoose models
- GraphQL API with automatic type generation
- Radix UI component library
Hour 3-4: Customize Core Pages
Modify the landing page, pricing tiers, and branding. This is straightforward HTML/CSS work. Use the AI assistant to speed through repetitive changes.
AI Prompt Example:
"Update the landing page hero section to describe my project: [description]. Keep the existing component structure, just change the text and add relevant icons."
Hour 5-6: Deploy to Production
Deploy to Vercel. Set up your domain. Configure environment variables. Test authentication and payments in production.
End of Day 1: You have a live website with working auth and payments. Not an MVP yet, but a solid foundation.
Day 2: Core Features (6-8 hours)
This is where AI-assisted development becomes a superpower. Instead of manually writing models, resolvers, components, and API routes, you describe what you want and let AI generate code that matches your existing patterns.
Morning: Database Models & API
Define your core data models. For example, if you're building a project management tool, you need Projects, Tasks, and Comments models.
AI Prompt Example:
"Create a Project model with fields: name (string), description (string), status (enum: active, completed, archived), owner (User reference), createdAt, updatedAt. Include GraphQL resolvers for CRUD operations and ensure it's assigned to the current user."
The AI reads your existing models (User, Team, etc.), understands your patterns (TypeComposer, security rules), and generates:
- Mongoose model with proper schema
- GraphQL resolvers (queries and mutations)
- Type definitions
- Auto-generated React hooks for the frontend
Afternoon: Frontend Components
Build the UI for your core features. List views, forms, detail pages. Again, let AI generate components that match your existing design system.
AI Prompt Example:
"Create a ProjectList component that fetches all projects for the current user, displays them in a grid with project name, status badge, and last updated date. Add a 'New Project' button that opens a modal. Use our existing Radix UI patterns."
End of Day 2: You have working CRUD operations for your main feature. Users can create, read, update, and delete data. Everything is styled consistently with your design system.
Day 3: Polish & Launch (4-6 hours)
Morning: Edge Cases & Validation
Add form validation, error handling, loading states. Test the happy path and the failure cases. Make sure users can't break things.
Midday: User Experience Polish
Add toast notifications for success/error states. Improve mobile responsiveness. Add empty states ("No projects yet. Create your first one!"). These details matter for perceived quality.
Afternoon: Deploy & Test
Push to production. Run through the entire user flow. Sign up, create data, test payments, verify email notifications. Fix any issues you find.
End of Day 3: You have a production-ready MVP. Real users can sign up, pay, and use your core feature. Time to start marketing.
What Makes This 10x Faster
Three things compound to create exponential speed:
1. Production-Ready Boilerplate
Authentication, payments, database, deployment—all solved problems. You focus only on your unique value proposition.
2. Context-Aware AI
AI that reads your entire codebase generates code that matches your patterns. No adapting generic outputs. It just works.
3. Architectural Consistency
Feature-driven structure means AI knows exactly where to put files. No decision fatigue. No architectural drift.
This Used to Take 3 Weeks
Week 1: Set up auth, database, payments.
Week 2: Build core features.
Week 3: Polish and deploy.
Now? Three days. That's 7x faster. And that's conservative. Some features I used to spend a week on now take an afternoon.
The bottleneck isn't your coding speed anymore. It's your idea validation, marketing, and customer conversations. Which is exactly where your time should go.
Ready to Ship Your MVP in 3 Days?
Get the same boilerplate and AI workflow I use. Start building today.