Making AI accessible in your products doesn't require a PhD. Here's how I integrated AI image editing into PhotoFy with practical examples...
## AI Is Just an API Call
That's the mindset shift. You don't need to train models. You need to use them well.
## Choosing the Right AI Service
For PhotoFy AI, I evaluated:
- **Stability AI** - Great for image generation
- **OpenAI DALL-E** - Versatile but expensive
- **Replicate** - Perfect for running open-source models
I went with Replicate for cost efficiency and model variety.
## Cost Optimization
AI APIs can get expensive fast. Here's how I kept costs down:
```typescript
// Cache results for identical requests
const getCachedOrGenerate = async (prompt: string, hash: string) => {
const cached = await cache.get(hash);
if (cached) return cached;
const result = await generateImage(prompt);
await cache.set(hash, result, 3600);
return result;
};
```
## UX for AI Features
1. **Set expectations** - Tell users AI isn't perfect
2. **Show progress** - AI takes time, show it
3. **Allow edits** - Let users tweak AI output
4. **Provide alternatives** - Generate multiple options
## Pricing AI Features
I charge $0.10 per generation and batch 10 credits for $0.99. Users feel they're getting a deal.
## Key Insight
AI is a feature, not a product. The product is solving user problems - AI just helps do it faster.
