Different models have different blind spots
Different AI models have unique blind spots that can lead to missed bugs. A recent multi-model review highlighted how Codex, Claude, and Gemini each caught different vulnerabilities in a code implementation. This underscores the importance of using a multi-model approach for thorough code reviews.
- ▪Codex flagged a Unix socket created without restrictive permissions, which could allow unauthorized access.
- ▪Claude identified an OAuth nonce placed on the wrong URL, risking a CSRF attack.
- ▪The multi-model consultation loop in Codev 3.0 allows for independent models to review code in parallel.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3829894) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Aliyah Mohammed for Codev OS Posted on May 19 with M Waleed Kadous Different models have different blind spots #ai #opensource #discuss #showdev One of the best arguments for Codev came from two specific "saves" earlier this year — bugs that no single model would have caught on its own. During a high-velocity sprint, @waleedkadous used Codev to ship a stack of features for the platform. The work looked ready to merge.
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