Mixing models is great for balancing strengths and spotting failure modes. But...

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Mixing models is great for balancing strengths and spotting failure modes. But don't blindly merge outputs. Synthesis often hides critical dissent or leaks data across providers. Keep your workflows transparent—don't let clever tooling mask your risk.