Why a Second AI Reviewer Changes the Result
The problem with AI review is not that models miss things. It is that you cannot tell which findings to trust.
The single-model problem
One model produces confident output whether or not it is correct. Teams respond by ignoring the bot, which removes whatever value it had.
What a second pass gives you
- Findings both models describe the same way move to the top.
- Findings the second model cannot justify move down or out.
- Issues the first model missed still get caught.
And it knows Supabase
Row-level security, service-role usage and policy design are checked explicitly, not inferred as generic database access.
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