| I’ve noticed a pattern with a lot of AI-assisted projects lately. People can build surprisingly capable apps using tools like Cursor, Replit, Loveable, etc... but many of those projects never actually make it to a real production launch. The apps work locally or in a demo environment, but the “last mile” tends to be where things stall: • infrastructure and hosting
• SSL and domain setup
• environment variables and secrets
• CI/CD pipelines
• scaling and monitoring
• security concerns I’ve spent most of my career working in software engineering and DevOps, and recently started helping indie builders and small startups solve this exact problem, getting their AI-generated apps shipped to production. I put together a page describing the typical deployment path and the kind of help I’ve been providing:
https://infiniumtek.com/vibes/ I’m curious what others here are seeing. For those building AI tools or AI-assisted products: Where does the launch process usually break down for you? Is it infrastructure, deployment complexity, security concerns, or something else? - Thomas |
The CI/CD gap matters a lot too. AI-generated code tends to skip the boring scaffolding: no branch protection, no secret scanning in the pipeline, no way to roll back safely if something goes wrong in prod. That stuff is invisible until it isn't.
What's the actual blocker for the projects you're seeing stall — is it the infrastructure setup itself, or is it more that the founders aren't confident the code is production-safe?