MCP Debat

Organize a four-phase debate among three AI models with different reasoning styles on: 'Should our retrieval system prioritize vector search or hybrid search?' Use constructive, challenge, closing, and synthesis phases. The host should flag equivocation and unsupported claims, then output a final recommendation, conditions, risks, and validation items.

A structured debate transcript plus a synthesized conclusion with recommendation, trade-offs, risks, and validation steps.

Have multiple AI models debate whether 'AI auto-summary should be enabled by default for new users' across four phases. One model should focus on UX, one on compliance and misinformation risk, and one on business metrics. The host should synthesize a decision recommendation and experiment plan while preventing mutual agreement bias.

A multi-perspective decision analysis with recommendations on launch, rollout strategy, and success metrics.

For the claim 'Remote work significantly improves team output,' run a four-phase multi-model debate. Have different models argue from data quality, causal inference, counterexamples, and management practice perspectives. The host must suppress sycophantic responses and produce the most reliable conclusions, evidence gaps, and next research steps.

A more robust research assessment showing which conclusions are credible and which still need evidence.