I was drafting beta invites when I realized my latest evaluation results had vanished.
Not a great look when you're about to ask people to test your AI model comparison tool. I refreshed the page, checked my code, even restarted the app. Nothing. The evaluations I'd run on the deployed version were simply gone.
That's when it hit me: I was about to invite beta testers to use an app that couldn't remember what they'd done.
The Replit Comfort Zone
When I started building QualRank AI three weeks ago, Replit was perfect. Need to spin up a Flask app? Done. Want to test an API integration? Just start coding. No Docker files, no deployment pipelines, no infrastructure headaches. It was like having training wheels that actually made you faster.
For rapid prototyping, this setup was brilliant. I could iterate quickly, share demos instantly, and focus on product instead of plumbing. Classic early-stage stuff.
But those disappearing evaluations? They revealed a fundamental problem with file-based storage on Replit's deployed apps. The platform wasn't persisting files between deployments, which meant every evaluation users ran would vanish.
The Breaking Point
The timing couldn't have been worse. I'd spent three weeks building something I was finally proud of—a clean interface for comparing AI models with detailed evaluation frameworks. The core functionality was solid. The UI was intuitive. I was ready to get real feedback.
Then I discovered my own evaluation results were disappearing.
I had two choices: hack together a database migration on Replit (only to face the same infrastructure limitations later), or finally make the leap to proper hosting. The builder in me wanted to find a clever workaround. The product person knew it was time to graduate.
You can't ask people to beta test something that forgets their work.
The Great Platform Hunt
Rather than panic-migrate to the first alternative, I decided to do this right. I evaluated five platforms systematically:
Vercel looked slick but was built for frontends, not Flask apps. Render had great Python support but would cost $50-70 monthly—steep when you're still pre-revenue. Fly.io was powerful but required Docker knowledge I didn't want to learn right now. DigitalOcean App Platform felt like traditional hosting with a modern coat of paint.
Then I found Railway.
Why Railway Won
Railway felt like Replit's grown-up sibling. Push code, get deployment. No Docker. No complex configuration. Just works—but with actual file persistence.
The pricing sealed it: usage-based billing starting around $15-25 monthly versus fixed costs elsewhere. When you're building something new, paying for what you actually use beats paying for what you might need.
But the real selling point? The migration path looked like 1-2 hours instead of 1-2 weeks. And crucially, Railway's file system actually persists data between deployments.
The 40-Minute Migration
Here's the thing about switching platforms: the anticipation is always worse than the reality.
I created a Railway account, connected my GitHub repo, and watched it auto-detect my Flask setup. Added a Procfile (one line), set environment variables, and deployed. The app was running in 20 minutes.
The other 20 minutes? Figuring out where to connect my custom domain. Classic developer experience—not the code, but the UI navigation that trips you up.
One runtime adjustment later (Python version specification), QualRank AI was live on Railway with persistent file storage, better performance, and room to grow.
The Real Victory
The migration itself was anticlimactic, which is exactly what you want. But the real win wasn't technical—it was mental.
I ran a test evaluation on the new deployment and refreshed the page. The results were still there. Deployed a small update. Results still there. That simple persistence unlocked everything.
Now I could send those beta invites with confidence.
Building in Public Lessons
Timing transitions is an art. I could have built on Replit for another month, but the beta timeline forced the decision. Sometimes external pressure creates better outcomes than internal planning.
Technical debt compounds quickly. Three weeks from start to "this won't work for real users" is a short timeline. The gap between prototype and product is often smaller than we think.
Migration anxiety is mostly fiction. I spent days dreading this change and 40 minutes executing it. The stories we tell ourselves about switching costs are usually scarier than the reality.
Platform decisions are reversible. Everything I built uses standard technologies—Python, Flask, file storage. I'm not locked into Railway any more than I was locked into Replit. Good architecture is platform-agnostic architecture.
What's Next
QualRank AI now runs on infrastructure that can handle real users instead of fighting against platform limitations. The app that started as a weekend experiment is ready for beta testing.
And honestly? It feels good to have the training wheels off just in time for the people who matter most to try it.