Relying on one LLM is a gamble. We mix models to leverage strengths and catch...

https://josuerwqt559.bearsfanteamshop.com/the-engineering-case-for-multi-model-workflows-moving-beyond-the-magic

Relying on one LLM is a gamble. We mix models to leverage strengths and catch errors via disagreement. But beware—synthesis can hide dissent or leak data across providers. Don't blindly ensemble; know where models fail before wiring them into your stack.