How I built a full supplement platform in 2 weeks (step-by-step breakdown)

Hey builders,

I shipped Good Supplements back in January - a platform for biohackers to discover and share supplement stacks. Took it from zero to deployed MVP in exactly 2 weeks. A lot of people on X asked me to break down the process, so here it is.

This walkthrough comes straight from my “Build Your First AI MVP” series.

If you want the full step-by-step on taking an idea to a live MVP in just 7 days (planning → design → build → deploy), you’ll find it all inside AI MVP Builders.

Here's what most builders get wrong about AI development:

They jump straight into coding without a plan. Then they wonder why their AI keeps building the wrong thing or why they're stuck rewriting everything halfway through.

I used to do this too. I'd get excited about an idea, open Cursor, and start prompting random features. Result? Messy code, confused AI, and weeks of rework.

The breakthrough came when I realized something:

AI is incredible at execution, but terrible at strategy. You need to do the thinking first, then let AI do the building.

Here's the exact workflow I used:

Step 1: Write a crystal clear project brief

Before touching any code, I spent 30 minutes defining:

• What the product does (supplement discovery platform)

• Who it's for (biohackers and wellness people)

• What problem it solves (organizing supplement stacks)

Prompt I used:
"I'm building a web app called Good Supplements that helps users organize supplement stacks and share them. Help me draft a structured project brief."

This becomes your north star. Every decision flows from here.

Step 2: Generate features with ChatGPT

I fed the brief back to ChatGPT and asked for a complete feature list.

Prompt:
"Here's my project brief: [brief]. Generate key features and technical requirements for this MVP."

Got back:

• User accounts and profiles

• Supplement search by name/category/benefits

• Custom stack creation and editing

• Community features (likes, bookmarks, sharing)

• Detailed supplement pages with ingredients and reviews

Step 3: Prioritize with MoSCoW method

This is where most people mess up. They try to build everything at once.

I organized features into:

• Must-Have: User accounts, search, stack creation, basic social features

• Should-Have: Recommendations, personalized suggestions

• Could-Have: AI-powered recommendations (future)

• Won't-Have: Real-time chat, advanced analytics (not MVP)

Prompt:
"Use the MoSCoW framework to prioritize these features for an efficient MVP launch."

This keeps you focused on what actually matters for validation.

Step 4: Build 100% of UI in Lovable first

Here's my controversial take: Build your entire frontend before touching backend logic.

I used Lovable to create every single page:

• Landing page with clean, trust-focused design

• User dashboard for managing stacks

• Search and discovery pages

• Stack builder interface

• Community sharing features

Why this works:

• You get a clear visual of what you're building

• Less distraction when adding backend logic later

• Faster iteration on design and user flow

• AI understands the full scope before building complex features

Step 5: Integrate Supabase through Lovable

Lovable has native Supabase integration. I set up:

• User authentication (signup, login, profiles)

• Database for supplement data and user stacks

• Social features (likes, bookmarks, sharing)

No manual configuration. No wrestling with API keys. Just works.

Step 6: Push Lovable to its limits

I built about 80-90% of the MVP inside Lovable before moving to Cursor. This included:

• All UI components and layouts

• Basic user interactions

• Database connections

• Simple business logic

Step 7: Use Cursor for the complex stuff

Finally moved to Cursor for:

• Advanced backend logic

• Performance optimizations for large datasets

• Complex state management

• API response optimization

The biggest challenge: Handling large supplement databases without killing performance.

Solutions I implemented:

• Lazy loading for images and descriptions

• Infinite scroll for search results

• Debounced search input (stops API spam)

• Smart caching for frequently accessed data

Step 8: Deploy and plan next features

Deployed with Vercel (takes 2 minutes). Then mapped out the roadmap:

• AI-powered supplement recommendations

• Personalized stack suggestions based on goals

• Expanded supplement database with more detailed info

The results:

Good Supplements went from idea to deployed MVP in 2 weeks. Not 2 months. Not 6 months. 2 weeks.

And it’s not some rough prototype. It’s a real platform people are actively using to track their supplement stacks (name and branding changed due to NDA).

Why this workflow is a game-changer:
Most founders spend months building MVPs that nobody wants. This approach lets you validate ideas in weeks, not months. You can test 6 ideas in the time it used to take to build one.

The AI-first development revolution isn't coming. It's here. The founders who adapt to these workflows will ship faster, validate quicker, and win bigger.

If you want to build MVPs this fast:

👉 Join AI MVP Builders: full series on building your first AI MVP, plus 4 other series, 20+ videos, daily support, and soon a library of business tools with $3M+ in perks.

👉 Need it built for you? IgnytLabs uses this same workflow for client projects, with higher quality, stronger systems, and tighter security, thanks to the AI-first dev team I’ve built over the past few months.

Keep building,
~ Prajwal