AI is rapidly moving from hype to real-world utility. Instead of just writing about it, I wanted to build something practical. That’s how I ended up creating an AI-powered passport photo maker a simple tool that solves a common problem with a clean, user-first approach.
The Problem I Wanted to Solve
Getting passport photos is surprisingly inconvenient. In Japan, photo booths are widely available but expensive. Many online tools either lock downloads behind paywalls or raise privacy concerns by asking for unnecessary permissions and sketchy websites asking for credit card details.
This made me think: Can I build a free, fast, and privacy-friendly alternative using AI?
The Approach: Keep It Simple, Keep It Fast
Instead of over-engineering, I focused on a lightweight architecture:
AI for background removal.
Browser-based processing for cropping and resizing
Predefined layouts for passport compliance
The key decision was to avoid building my own AI model. Instead, I used existing APIs and focused on integrating them efficiently into the user workflow.
This approach helped me:
Reduce development time
Avoid infrastructure overhead
Deliver immediate value
From Netlify to Blogger: A Strategic Shift
Initially, I deployed the tool on Netlify. It worked great from a technical standpoint. It's fast, scalable, and easy to deploy.
However, I later moved the tool directly into Blogger.
Why?
SEO advantage: Keeping everything under one domain improved discoverability
User journey: Blog readers can directly access the tool without switching domains
This shift made me realize something important:
- Distribution and discoverability often matter more than infrastructure perfection.
Where AI Actually Helped
The most interesting part was not the AI itself, but how it was used:
Automatically removing complex backgrounds
Standardizing images into passport formats
Reducing manual editing effort to near zero
This reinforced a key idea:
- AI is most powerful when it removes friction from simple tasks.
DevOps Mindset in a “Simple” Project
Even though this is not a large-scale system, DevOps thinking still applied:
Designing for minimal backend dependency
Optimizing for performance and load time
Structuring the project for easy updates and iteration
After moving to Blogger, I lost automated CI/CD, but gained tighter integration with my content platform. It became a trade-off between automation and control vs reach and simplicity.
Key Learnings
AI is an enabler, not the product
The real value comes from solving user problems, not showcasing AI.Frontend can do more than you think
Modern browsers are powerful enough for many “AI-like” experiences.Don’t overbuild early
Start simple, validate, then scale.
Building this tool was a great reminder that you don’t need complex systems to create meaningful AI products. With the right balance of AI, cloud thinking, and DevOps principles, even a small idea can turn into something genuinely useful.