The Problem I Discovered
The skincare industry is overwhelming. Consumers face thousands of products with ingredient lists that look like chemistry experiments. I noticed my friends constantly asking "is this ingredient safe?" - that's when the idea hit me.
Planning & Tech Stack Decision
After validating the idea with potential users, I chose a stack I knew well:
- Frontend: React with TypeScript for type safety
- Backend: Node.js with Express
- AI: OpenAI GPT-4 for ingredient analysis
- Database: MongoDB for flexible document storage
Development Journey
Week 1: Backend API and AI Integration
The first week was all about getting the AI working. I integrated OpenAI's API to analyze ingredient lists and return safety scores.
const analyzeIngredients = async (ingredients) => {
const response = await openai.chat.completions.create({
model: "gpt-4",
messages: [
{ role: "system", content: "You are a skincare expert..." },
{ role: "user", content: `Analyze: ${ingredients}` }
]
});
return response.choices[0].message.content;
};
Week 2: Frontend Development
Built a clean, mobile-first interface. Users can paste ingredient lists or scan product labels.
Week 3: Testing and Refinement
User testing revealed the need for simpler explanations. I added a "explain like I'm 5" mode.
Week 4: Launch Preparation
Set up payment integration with Lemon Squeezy, prepared marketing materials, and soft-launched to my newsletter.
Launch Results
- Week 1: 127 signups, $240 MRR
- Month 1: 500+ users, $800 MRR
- Month 3: 2,000+ users, $2,400 MRR
Key Takeaways