Me too, because I hear a lot of experiences like yours as well. It might be opinionated architecture not fitting the training norm, size of legacy repos/project

Me too, because I hear a lot of experiences like yours as well. It might be opinionated architecture not fitting the training norm, size of legacy repos/projects, language, or whatever else. For what it's worth I/we do much less manual coding now too, but it almost always takes a handful of re-prompts to reach expectations. We can do hooks to reduce superfluous comments or do a second specs-adherence pass, or write failing tests first, but other discrepancies aren't uniform enough to enforce in prompts or context. I'd love to know the difference too. Or whether long term velocity would be higher by vibing through PRs and deal with issues when things explode or refactor down 2M lines of LLM creep after the fact.