thinking-parliament

Multi-agent deliberation tackles complex strategic decisions by engaging diverse AI models to simulate varied perspectives, ensuring comprehensive analysis and preventing groupthink. This approach dynamically adjusts intensity based on problem confidence scores.

Confidence-based routing in AI decision making dynamically adjusts deliberation intensity by evaluating a confidence score for the problem. This routing system ensures comprehensive analysis by scaling computational effort to match the uncertainty of complex problems.

Prevent groupthink when analyzing complex problems by orchestrating multiple AI agents with distinct models like Claude, Gemini, Llama, and DeepSeek. This multi-agent approach leverages cognitive design patterns to ensure genuine perspective diversity.

Yes, you can use different AI models together to explore a product pivot strategy. This approach convenes a parliament of AI agents to explore all angles, identify risks, and propose well-reasoned options for strategic decisions with significant uncertainty.

Context gathering for multi-agent deliberation utilizes pre-step context retrieval to ensure agents deliberate with comprehensive information. This context injection phase occurs before the axiom-style multi-turn thinking process begins.

Use multi-agent diverse perspective deliberation when facing complex problems that require varied viewpoints and involve significant uncertainty. It is particularly effective for strategic decisions where preventing groupthink and exploring all angles is critical.