1. **Ensemble for Interpretations:** For each factual "Observation" identified, the AI will internally generate multiple sets of "Interpretations." These sets will then be synthesized by the AI into a single, more robust set of final interpretations for that observation. This aims to broaden the perspectives considered for each piece of evidence. 2. **Meta-Reflection Layer:** After the core analysis (observations with synthesized interpretations, and alternative theories) is complete, a new "Meta-Reflection" step will be added. In this step, the AI will review its entire output for the query, aiming to: - Identify the most consistently supported conclusions. - Highlight areas of significant conflict or uncertainty within its own generated analysis. - Comment on potential underlying assumptions or even "blind spots" that might be inherent in the analysis, touching upon the dynamic and sometimes biased nature of "consensus."