Zero to One in AI: How I Built and Launched Two AI MVPs in 4 Weeks

You don’t need a 10-person team to build an AI product. You need clarity, the right tools — and obsession with the problem you're solving.

How It Started

In early 2025, I challenged myself with a bold goal: Build and launch not one, but two AI-powered MVPs in under a month.

• Sattvahar – a mindful plant-based food discovery platform built on trust and transparency.

• MyFortivo – a mental wellness companion that blends AI with therapeutic tools to help users manage stress, anxiety, and emotional overwhelm.

Both ideas came from real unmet needs I saw in the world around me.

One focused on what we put into our body, the other on what we carry in our mind.

And both shared one thing in common:I had no engineering team, no fancy VC backing - just my product skills, empathy, and a powerful no-code AI stack.

Week 1: From Clarity to Toolstack

First, I asked:

• What's the smallest version of this product that can solve something real?

• Can I launch it without waiting on anyone?

Tools I chose:

Purpose	Tool	Why
AI Brain	ChatGPT (GPT-4 API)	Fast, powerful, and flexible for conversational UX and emotional guidance
Logic Layer	Lovable	My go-to low-code platform to orchestrate flows, AI prompts, branching paths
Memory / DB	Supabase	For securely storing user mood logs, self-assessments (PHQ-9/GAD-7), meal preferences
Payments	Stripe	Future-proofing: whether it's Sattvahar meal plans or therapy session bookings
Hosting	Vercel	Instant, stable deployment of landing pages and APIs
Dev Collab	Git + GitHub	For version control when engineering joined post-MVP phase

PM Insight: Don’t waste the first week building features. Use it to define value loops and sketch the fastest, truest path from user pain to relief.

Case Study 1: Sattvahar — Clean Eating, Reimagined with AI

Problem:

People wanted to eat healthy, clean, plant-based food — but couldn’t trust delivery apps. Too many hidden charges, fake reviews, and no real transparency on how food was made.

What I built:

• A conversational food discovery flow where users could:

  • Set dietary goals

  • Filter by allergies, intolerances, ayurvedic needs

  • Discover honest, local vegan kitchens

• AI-powered transparency card that explains:

  • Where the food came from

  • How it's made

  • Delivery CO2 impact (coming soon)

    
    

Stack in action:

Lovable handled the food flow, ChatGPT generated smart meal explanations, and Supabase stored preferences and history.

🧭 PM Reflection: People don’t need a fancy app. They need to feel safe about what they’re eating. I focused on trust, not trendiness.

Case Study 2: MyFortivo — A Therapist in Your Pocket (Almost)

Problem:

Most people don’t want to “go to therapy” — but they do want to feel heard, guided, and supported when things get overwhelming.

What I built:

• A safe, AI-guided emotional wellness assistant

• Features:

  • Daily check-ins with mood tracking

  • Self-assessments (PHQ-9, GAD-7)

  • Therapist discovery (human), not just chatbot fluff

  • Pre/post therapy journaling guidance

    
    

Real innovation:

• Smart journaling prompt engine via ChatGPT

• Personal reflection tracker stored securely via Supabase

• Optional therapist booking via Stripe (pilot only)

PM Reflection: In wellness, language matters. I spent hours testing prompts that felt supportive, not robotic.

Testing with Real Users

Once the MVPs were live, I invited early users via:

• LinkedIn posts + DMs

• Closed WhatsApp communities

• Mental health Slack groups (for MyFortivo)

  
  

Feedback:

• Sattvahar: People loved the idea of “food with clarity.” But they wanted real-time delivery ETAs and true ratings.

• MyFortivo: Users felt emotionally safe — but asked for memory, journaling history, and multi-language support.

I logged all feedback in Airtable and iterated within Lovable in less than a day.

PM Truth: Speed wins trust — but listening wins loyalty.

Final Results (In 4 Weeks)

• 2 fully working AI MVPs

• 60+ beta users across both products

• 3 repeat therapy bookings via MyFortivo pilot

• 90% completion rate on PHQ-9 check-ins

• 100+ meal discovery interactions on Sattvahar

All without writing a single line of code — until it was actually needed.

What I Learned

1. AI Products Live or Die on Prompt Design

I tested 20+ iterations per feature. Tiny prompt changes = huge user experience changes.

2. No-Code ≠ No Strategy

Lovable and ChatGPT let me move fast, but product sense — and user empathy — made it land.

3. Solve One Pain First

In both products, I resisted the urge to add more features. I focused on one core user promise.

4. You Can Ship More Than You Think

Two MVPs in 4 weeks. With clarity, feedback, and a fast loop — it’s absolutely doable.

What’s Next

• Sattvahar: Launching curated vegan meal plans, adding user reviews, and real-time delivery tracking

• MyFortivo: Expanding to multilingual support, integrating voice journaling, and mental health nudges via WhatsApp

And most importantly — continuing to build products that serve real needs, not just demo well.

You don’t need to code to launch a real AI product.

You need:

• A problem worth solving

• A toolkit that lets you move fast

• And the courage to ship, listen, and improve

Zero to one isn’t about perfection.It’s about presence.Start where you are. Build what matters.