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Episode Title: The AI Synthesizer Accountability Gap: What Perplexity's Model Council Needs

Episode Notes (paste into the 4,000-char field):

Two hosts unpack a governance case study on Perplexity's Model Council, the multi-model AI feature that dispatches Claude, GPT, and Gemini simultaneously and synthesizes their answers into one response.

The central question: when an automated synthesizer combines three frontier model outputs before any human reads them, who governs what it includes, excludes, and changes?

The conversation covers five areas. First, why parallel multi-model dispatch is the correct architecture for consequential decisions and what Perplexity got right. Second, the synthesizer accountability gap, including seven documented fa ...