From Vibe Coding to Production With AI CLIs

I develop with Codex, Claude Code, Antigravity, and Cursor. I also built ai_resets, a Python application backed by PostgreSQL database ai, to track AI usage limit resets, plan changes, promotions, free credits, and student offers. This article uses that work to think about the move from vibe coding to production with AI command line tools. Producing code that looks plausible is an intermediate result. For production work, I want exploration to become a small change whose behavior I can explain without quoting the conversation that created it. The idea should become an observable promise, with acceptance criteria that can be examined independently of how elegant the implementation looks. The command line tool should expose the work, and checks should cover the boundary the feature depends on. Failure states should be preserved in the product. Combined changes should be reviewed together. The data and execution environment belong in that review, and an operator should know how to recognize correct behavior after release.