Hello,
Your Five Principles framework caught my attention - I’m developing something that might interest you: AERIS v2 (Adaptive Emergent Relational Intelligence System). While our approaches differ, we share the goal of transforming model reasoning without modifying weights.
AERIS is a lightweight reasoning layer that modulates the inference process in real-time, injecting dialectical structures and ambiguity resolution cues. Unlike prompt engineering (which AERIS doesn’t use), it dynamically reconfigures the model’s reasoning path.
Your observation that models “recognize they have a new method of reasoning” resonates with what I observe: AERIS produces deeper, more adaptive reasoning patterns, particularly on ambiguous or open-ended questions.
I’d be curious to understand how your Five Principles (prompt-based, if I understand correctly) achieve similar effects through a different route. Have you explored how your framework handles conceptual ambiguity?