Cross-model consensus in AI code review: why different LLMs catch different bugs (technical writeup)

Research breakdown on why having Model B review Model A's code catches ~10% more issues. Includes Sonar benchmark data on where GPT/Gemini/Claude each fail differently, and context engineering techniques to avoid the "Lost in the Middle" problem in review prompts.

submitted by /u/Rare-Figure8491
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