The Approach
The Premise
This inquiry began from Arun’s long-standing curiosity: What is the true structure of intelligence?
As a Cognitive Architect, Arun sees intelligence not as a set of skills or outputs, but as an architecture, an arrangement of primitives and relationships that determines how intelligence emerges, stays aligned, and adapts under disturbance.
The Architecture of Intelligence is:
Identity-bound: Shaped by values, goals, and self-definition.
Cognition-driven: Guided by reasoning, framing, and decision-making.
Language-enabled: Communicated through precise representation and meaning transfer.
Behavior-tested: Strengthened by feedback and iteration.
Meta-aware: Able to observe and refine its own processes.
Cognitive Stacks exists to make this architecture visible, structured, and discussable, as the first step toward a shared foundation for understanding intelligence.
What We Are Doing Now
Cognitive Stacks is an independent research nucleus initiated to bring clarity and structure to the Architecture of Intelligence.
Our current work focuses on:
Mapping the Components: Identifying and describing the primitives and their interconnections.
Developing Conceptual Frameworks: Creating models that can be examined, refined, and applied in discussion.
Opening a Research Agenda: Engaging with thinkers, practitioners, and researchers to stress-test and evolve these ideas.
This is not an academic lab.
It is a deliberate, small-scale exploration led by a Cognitive Architect with the goal of establishing long-term intellectual foundations.
Why This Matters
Without understanding the Architecture of Intelligence:
AI may gain capability without alignment.
Human and organizational cognition will remain reactive and fragmented.
Progress will lack the structural base needed to be scalable and self-improving.
Defining the architecture provides a shared structure for thinking, enabling intelligence to be more reliable, adaptable, and coherent across human and machine contexts.
The Road Ahead
In the near term, Cognitive Stacks will:
1. Map the Architecture: Produce a coherent, documented view of the key components and how they interact. (Outputs: foundational diagrams, working papers, open discussion notes).
2. Refine the Models: Stress-test conceptual frameworks across multiple disciplines and contexts. (Outputs: case studies, refinement sessions, iterative model updates).
3. Create a Common Language: Establish precise terminology, definitions, and visual structures to make the Architecture of Intelligence accessible and teachable. (Outputs: glossary, visual maps, explanatory briefs).
These steps will create a living, evolving body of work, one that others can engage with, critique, and help refine.