Abhisek Dubey

Building a Minimum Viable Product (MVP) is easy in theory. In practice, it’s a series of brutal compromises.

Earlier this year, I built an AI-powered matrimony platform designed to eliminate fake profiles. I didn't have a backend team, an infinite budget, or six months to polish every button. I had a deadline, limited funds, and my own skills as a frontend-heavy engineer.

This is how I navigated those constraints to build a production-ready MVP.

The Reality of Constraints

Most MVP advice assumes you have a balanced team. My reality was different:

**Time**: Every week spent in development was a week of overhead with no revenue.

**Budget**: I had to be extremely selective about paid services and cloud costs.

**Skills**: I am deep in React, Next.js, and UI architecture. My backend skills are functional, but I’m not a systems engineer.

I had to play to my strengths while finding a "force multiplier" for my weaknesses.

AI as a Force Multiplier

I don't use AI to write my entire codebase. I use it as a senior-level partner for the parts of the stack where I’m less efficient.

For this project, I used AI to:

**Draft API Contracts**: I defined the frontend needs, and AI helped me design the MongoDB schemas and Express routes to match.

**Debug Complex Logic**: When a compatibility algorithm felt sluggish, I used AI to identify bottlenecked queries.

**Validation & Security**: AI helped me write robust validation schemas (Zod/Joi) that I might have otherwise rushed.

By using AI responsibly, I focused my "human energy" on the product experience and UI architecture—the things that actually make users trust a matrimony platform.

Architecture: Frontend-First

When you’re a frontend expert, "Frontend-First" isn't just a preference; it's a strategy.

I focused on the Critical Path: What is the most important thing a user does? For us, it was profile verification and matching. I built the UI for these flows first, using mocked data to feel the product before the backend even existed.

This allowed me to iterate on the user experience without being blocked by API development. Once the flow felt right, I "filled in" the backend.

The Tech Stack: Pragmatism Over Hype

I chose a stack that maximized speed and stability:

**Next.js**: The obvious choice for SEO, performance, and a unified development experience.

**Tailwind CSS**: For rapid UI development without fighting with stylesheets.

**MongoDB**: Schema flexibility was key. As the MVP evolved, I didn't want to spend days on SQL migrations.

**OpenAI API**: Used for profile generation—a core feature that would have taken months to build manually.

I didn't choose these because they were trendy. I chose them because they allowed me to move fast and stay within budget.

What I Intentionally Did NOT Build

A senior engineer knows that what you *don't* build is just as important as what you do. To launch quickly, I cut:

**Complex Microservices**: I stayed with a monolithic repo. No need for the overhead of service communication yet.

**Custom Auth**: I used proven libraries. Rolling your own auth in an MVP is a liability.

**Perfect Analytics**: I stuck to basic tracking. I didn't need a custom data lake on Day 1.

Early Feedback & Learning

The goal of an MVP is to learn. By launching a "Frontend-First" product, I realized early on that users cared more about the *quality* of profile descriptions than the speed of the matching algorithm.

If I had spent three weeks optimizing the backend first, I would have wasted time on a feature that wasn't the primary driver of user satisfaction.

What's Next: The V2 Roadmap

Now that the MVP is live and serving 25k+ users, the focus shifts:

**Refactoring for Scale**: Moving those AI-assisted backend routes into a more robust architecture.

**Automated Testing**: Now that the features are stable, it’s time to lock them down with comprehensive testing.

**Enhanced AI Integration**: Moving beyond basic profile generation to more predictive matching.

Key Takeaways

If you’re building your own MVP under constraints, remember:

**Skills are your leverage**: Play to your strengths (for me, the frontend) and use AI to fill the gaps.

**Scope is a weapon**: Use it to cut anything that doesn't serve the core user goal.

**Decision-making > Tools**: Choosing the "right" tool matters less than understanding the tradeoffs of that choice.

Building this platform wasn't about being the "best" coder; it was about being the most effective product owner.

Building an MVP Under Real Constraints: A Frontend-First, AI-Assisted Approach