# Scoping AI-Assisted Work: Why 'Quality Over Tools' Isn't Enough > Source: > Published: 2026-07-18 18:00:12+00:00 A debate surfaced recently in open source: should projects accept contributions regardless of whether they were AI-assisted, as long as the output quality is high? It's a fair question that touches something real about how we work now. But in practice, it misses a few critical things. **The Maintenance Burden Doesn't Disappear** If a human writes unreadable code, that's a hiring or training problem. If AI generates unreadable code, you've got a different problem: the person reviewing it might not fully understand it either, and neither might the AI that generated it next time. Code review becomes theater instead of verification. **"Quality" Needs Definition Earlier** When you scope a piece of work with a human, you can say "make it maintainable, document your reasoning, follow the style guide." Those are instructions a skilled person understands. With AI-generated work, quality often means "passes tests and runs", not "someone else can confidently modify this in six months." The goalposts shift without you noticing. **The Real Question Is Ownership** If something breaks in production, who debugs it? If a team member leaves, who explains the design? If requirements shift, who refactors it safely? These aren't abstract. They determine whether a contribution actually reduces work or just defers it. The honest take: AI contributions are fine. But the bar for review should go UP, not stay the same. You're not just checking that it works; you're checking that it's maintainable by humans who might not know why it was written that way. That's extra work upfront, and it's worth pricing it that way.