That prototype actually works. Getting it to production is different.
📰 Dev.to AI
Learn why AI-built apps feel fast initially but slow down when they hit real users and how to overcome this issue
Action Steps
- Identify the limitations of your AI-built app's infrastructure
- Migrate your data to a self-managed infrastructure to optimize queries and backups
- Configure database schema and auth flow for scalability
- Test and monitor your app's performance with real users
- Apply optimization techniques to improve your app's speed and reliability
Who Needs to Know This
Developers and DevOps teams can benefit from understanding the limitations of AI-built apps and how to optimize them for production
Key Insight
💡 AI-built apps often rely on the builder's infrastructure, which can limit optimization and scalability
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🚀 AI-built apps can feel fast at first, but slow down with real users. Learn how to overcome this and optimize for production 🚀
Key Takeaways
Learn why AI-built apps feel fast initially but slow down when they hit real users and how to overcome this issue
Full Article
Why Your AI-Built App Feels Fast Until It Hits Real Users You shipped something in a weekend. Lovable, Bolt, or Base44 made it possible. The builder handled the scaffolding, the database schema, the auth flow. You iterated fast. Things worked. Then you invited actual users. That's when you hit the first ceiling: your data lives on the builder's infrastructure. You can't see the database. You can't optimize queries. You can't back it up to your own systems. You're rent
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