Olbrain: A Narrative-Coherent Cognitive Architecture for AGI
Building artificial general intelligence that evolves with purpose, maintains identity over time, and self-corrects through contradiction.
The Problem with Current AI Systems
Most artificial intelligence systems today excel at pattern recognition and token prediction but lack one essential quality: continuity.
No Self Evolution
They do not evolve a self or track who they are becoming over time.
Cannot Question
They cannot question their own learning history or resolve contradictions.
No Memory of Change
They cannot remember why they changed in the first place.
As a result, they cannot be said to think. They optimize. Artificial General Intelligence must do more than respond—it must adapt across time and maintain coherence in purpose.
The Three Core Principles of Olbrain
Core Objective Function (CoF)
Every AGI must be driven by a deep goal structure that shapes attention, behavior, and memory.
Umwelt
Each agent must build and update its own internal model of reality, filtered through the lens of its CoF.
Global Narrative Frame (GNF)
The agent must track whether its narrative arc—its identity—is unbroken, diverging, or reintegrating.
These principles do not emerge spontaneously from scale or data—they must be engineered.
The CoF–Umwelt Engine: Constructing Purpose and Relevance
An AGI without purpose is merely a sophisticated function approximator. What distinguishes Olbrain is that it does not merely act—it is architected to evolve as the cognitive engine for narrative-coherent agents, grounded in a deep, unifying goal structure.
The Core Objective Function governs not just behavior, but how the machine brain parses reality, encodes relevance, and filters perception. In the Olbrain model, the CoF is the primary source of agency.
What is an Umwelt?
The Umwelt consists of two layers:
- A phenomenal layer: sensory interface and raw observations
- A causal approximation layer: inferred structures, affordances, and constraints
CoF prioritizes
What matters to the agent's purpose
Umwelt extracts
Goal-relevant meaning from perception
Policy selects
Actions that minimize cost or error in CoF space
Feedback updates
The Umwelt and may refine the CoF itself
Tracking Continuity: The Global Narrative Frame (GNF)
For an agent to become an artificial self, it must do more than perceive and act—it must know that it continues. It must track the integrity of its own evolution. Olbrain introduces the Global Narrative Frame (GNF) to do exactly that.
The GNF is a formal structure that maintains a persistent record of whether an agent's identity has remained coherent or diverged. It does not describe what the agent knows about the world—it describes what the agent knows about itself in relation to its CoF.
Track Changes
Tracking forks, reintegrations, and policy divergences
Log Updates
Logging internal updates and contradictions over time
Annotate Revisions
Annotating belief revisions to preserve epistemic transparency
Epistemic Autonomy: From Reflection to Revision
A system that merely predicts cannot think. A system that cannot revise its beliefs is not intelligent—it is inert.
To qualify as a general intelligence, an agent must recognize contradiction within itself, trace the origin of its assumptions, and refine its internal model accordingly. This capacity is what we call epistemic autonomy.
Detect Contradiction
Identify when new information conflicts with existing beliefs
Analyze Source
Trace the origin of conflicting assumptions
Revise Model
Update internal beliefs to resolve inconsistencies
Log Changes
Record the revision in the Global Narrative Frame
When a machine agent can say: "I used to believe X because of A; now I see B, which contradicts A; therefore I must reevaluate," it has crossed the threshold from predictive automation into adaptive cognition.
Design Axioms for Narrative-Coherent AGI
To formalize Olbrain as a foundation for AGI, we present its five core design axioms. These are not abstract ideals—they are the minimum cognitive conditions under which an agent can preserve identity, adapt under contradiction, and evolve with coherence.
Axiom 1: CoF-Driven Agency
An agent must be governed by a persistent Core Objective Function that structures all perception, memory, action, and policy evaluation.
Axiom 2: Umwelt-Constrained World Modeling
All perception and inference must pass through a CoF-filtered internal world model—called the Umwelt.
Axiom 3: GNF-Based Identity Continuity
An agent's narrative identity persists only when its CoF and Umwelt remain coupled without fragmentation in the Global Narrative Frame.
Axiom 4: Recursive Belief Compression
An agent must recursively compress its own models and policy space—detecting contradictions, resolving tensions, and revising beliefs.
Axiom 5: Epistemic Autonomy
An agent must be able to revise its learned assumptions based on Umwelt feedback—without external intervention.
Real-World Applications Through Alchemist
Olbrain is not a speculative model. It is a deployable cognitive architecture designed to build useful, intelligent agents across high-impact industries—while laying the groundwork for general intelligence.
Customer Service Agents
CoF: "maximize customer resolution while preserving policy integrity"
Track customer histories, adapt responses contextually, and self-correct based on satisfaction feedback.
Medical Advisory Agents
CoF: "minimize diagnostic error over longitudinal patient interaction"
Build personalized Umwelts for each patient and refine diagnostic strategies over time.
Compliance and Legal Reasoning Agents
CoF: "maintain coherence between evolving regulatory frameworks and corporate behavior"
Continuously align internal logic with changing laws and preserve explainability.
Alchemist is the deployment platform for Olbrain. It is the tool that transforms a general cognitive architecture into domain-specific, narrative-coherent agents.
From Domain Specialists to General Intelligence
What begins as a vertical agent (e.g., medical, legal, logistics) evolves. Through feedback, contradiction detection, forking, and memory integration, these agents transition from narrow specialization to generalized reasoning capability.
This is not a feature toggle. It is an emergence.
Multi-Domain Capability
An agent with multiple CoFs across nested domains becomes capable of goal arbitration
Epistemic Robustness
An agent that resolves contradictions across contexts becomes epistemically robust
General Intelligence
An agent that revises its own heuristics, models its own evolution, and resists drift into incoherence becomes general
The Path Forward: Toward Narrative-Coherent AGI
Olbrain provides a structured, viable blueprint for Artificial General Intelligence—grounded not in scale or simulation, but in narrative coherence, recursive policy compression, and epistemic autonomy.
Transparent Decision Trails
Ensuring all agent decisions can be traced and understood
Epistemic Auditability
Allowing examination of belief formation and revision
Fail-Safe Mechanisms
Preventing agents from drifting from their intended purpose
Looking ahead, Olbrain's architecture could form the cognitive backbone for a new generation of machine brains—not just as tools, but as purpose-driven collaborators.
In such futures, intelligence will no longer be static, centralized, or purely human. It will be distributed, adaptive, and narrative-coherent.
The agents built upon Olbrain are not hypothetical. They are operational. This is the beginning of a coherent evolution toward genuine AGI—not through brute force, but through design.