Let’s face it: by the time I manually ship version 1.0 of a product, the AI-assisted version could have been deployed 10x faster. By then, enough real-world feedback would have surfaced to identify the major issues, and tools like Claude Code would make it possible to fix and ship version 2.0 at an incredible pace.

This isn't really related to AI because it relates to manually coded things just as much, but on this point specifically this is only true for your very early I-gave-it-to-a-bunch-of-interested-people-to-try customers. It's much less true for your first paying customers, especially if the 'major issues' make their pain worse (e.g. data loss, time wasted, etc). You lose those ones for good, or until there's a critical mass of social proof to tell them the early problems are solved.

'I can dash out an early prototype with AI and then fix it later' is a dangerous mindset. If you're working in a small market with a limited number of customers you might piss off enough people that you won't be able to recover. There still has to be some level of quality. But it is a balance.