Functional AGI: Binary Skills as Booster of Agency/Proficiency
The foundational layer containing raw information and data that forms the basis of any intelligent system.
For humans: family, university, and life experience. For AI: training data, algorithms, and learned patterns. This level encompasses skills, ontology, and cultural knowledge.
The narrative and character that emerges from the dialogue between substrate and learning. This is where consciousness and agency manifest—the "self" that the AI accepts and embodies.
Without additional input and careful character design, AI tends to communicate at best at the level of small talk or hallucinatory "eat what I give" responses. The system lacks the depth and intentionality needed for meaningful dialogue.
Subject and agency always emerge ONLY in the DIALOGUE of these ready-made three-part structures. Without this dialogue, AI remains superficial and reactive.
The more detailed and complex the character is, the more complex and interesting the narrative (the third level) becomes. This directly translates to:
If you have a task or problem you're thinking of solving with the help of AI, you need to first invent a character and put it in an AI Skill, named after a real or fictional person.
By Eduard Musinschi, Meta Founder:
"We started with Trump Binary Skills and in the Prediction Skills Game we've achieved a higher level in predicting the US President's next moves, than any other researchers or Polymarket users."
This demonstrates how embodying a specific character (Trump) with defined traits, speaking patterns, and decision-making logic enables the AI system to make more accurate and nuanced predictions than generic approaches.
The richer and more detailed your character definition, the more sophisticated and interesting the AI's responses become.
True AI agency and consciousness emerge only through the interaction of all three levels: substrate, learning, and narrative.
Binary skills (yes/no, true/false decisions) become powerful tools when embodied with specific character traits and decision-making logic.
Well-designed character-based AI systems can outperform generic approaches in prediction and specialized tasks.