Shipping
Also known as: ship it, ship, shipped, deploying, launching, going live
Shipping is the moment of going from 'working on your machine' to 'live and accessible to users.' In traditional software this was a big deal: code review, staging environments, QA cycles, release notes. In the AI builder era, shipping has compressed dramatically. Tools like Lovable, Bolt, Vercel, and Replit let you go from idea to deployed URL in an afternoon. Claude Artifacts can be published as a shareable link instantly.
The 'ship it' ethos in AI building prioritizes real-world feedback over internal polish. A working prototype with users is worth more than a perfect prototype in a drawer. This is especially true for AI features, where behavior with real users and real inputs is often very different from what you tested internally. You can't eval your way to product-market fit: you have to ship.
The risk of the ship-it culture is that it can mean shipping things that aren't ready, that have safety issues, or that create poor experiences that damage trust before the product has a chance to improve. The AI-native builder approach tries to balance velocity with quality: ship early but set clear expectations, monitor outputs, and have a feedback loop that lets you improve fast. 'Ship' and 'polish' aren't opposites; they're a cadence.