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Code migration is where AI projects actually fail, not in the lab

DEV Community·Nometria·29 days ago
#uvMdJRtC
#ai#webdev#api#sdk#production#real
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The Gap Between "Built" and "Production-Ready" Nobody Talks About You shipped your app in Lovable in two weeks. It works. Users are signing up. Revenue is real. Then you hit the first production problem: your database lives on their servers, you can't roll back a bad migration, and scaling means rebuilding on real infrastructure anyway. This is the moment every AI-built app hits the wall. Here's what actually happens. AI builders optimize for iteration speed, not production resilience. They excel at getting from idea to working prototype fast. But production has requirements builders don't expose: rollback capability, deployment history, database ownership, CI/CD pipelines, compliance, custom infrastructure. When SmartFixOS migrated from Base44, they discovered their customer data and job records were locked into a proprietary database. When Wright Choice Mentoring scaled to 10+ organizations, they realized they had no way to version control changes or roll back if something broke.…

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