state structure, making the design and presentation of information through generic, static interfaces far less effective than future, conceptually optimized approaches. Today's systems are designed for mass use, with individual differences and a detailed understanding of the brain's decision-making often considered secondary. 

Three Types of Cognitive Friction

Decision Friction

The human brain differs significantly from an LLM, contrary to repeated claims that Artificial Neural Nets mirror the brain in processing and structure. Decision friction (as an overarching concept) occurs when interfaces require users to 'navigate' the brain's natural data/information interrogation and decision-making processes, and artificial system design and function mismatches. A clear example is when critical decision-relevant information is presented in a way that exceeds the brain's working memory capacity—whether it's unrelated to emotion or outcomes, scattered across multiple screens, buried in hierarchical menus, or displayed in abstract formats that obscure natural relationships or outcomes—decision friction increases significantly. Yet, the pursuit of data-dense interfaces has continued despite scientific evidence of its futility. 

The key to designing future systems is the uniqueness of decision makers and their connection with rapidly advancing AI systems that have world models, can reason, and operate in virtual settings. Therefore, the measure for next-generation systems must be N=1. This simple equation, supported by various scientific fields, paves the way for a new type of in-system, dynamic design driven by the AI itself.

Recall Friction

Recall friction occurs when interfaces fail to utilize the brain's natural memory formation and retrieval processes, such as the use of time sequencing, its consistent nature, associative networks, spatial relationships, and emotional ties. All of this is dynamically filtered through the individual's unique interrogation methods, psychological state, trait structure, and the relationship between the brain's left and right hemispheres as described by Ian McGilchrist's seminal research.    

With the new understanding of N=1, science, and Agentic AI capabilities, the future of UIs involves dynamic, real-time, and personalized construction to significantly reduce recall friction in ways native to the brain's learning and sense-making.

Processing Friction

Processing friction occurs when UIs overwhelm cognitive capacity or present information in ways that conflict with the brain's natural data processing. Scientific studies indicate that working memory can hold about four objects at once, with two managed by the left hemisphere and two by the right. When UIs present exponentially more information in dense formats, processing friction occurs immediately and often increases as users analyze multi-dimensional, multi-temporal data.  

Edward Tufte, considered the father of visual analytics, promoted the idea that every inch of space should 'speak to the data' and emphasized high data density in visualization. However, this approach in design thinking has not led to improved understanding, awareness, or decision-making. The reason is straightforward; although it sounds appealing, it conflicts with the brain's natural decision-making processes and system functions. The brain is lazy and not designed to use its System 2, as described by Daniel Kahneman in his seminal works. Instead, the brain prefers to 'thin slice' (a term popularized by Malcolm Gladwell) and make quick decisions without full context, relying on what it believes to be true with the Left hemisphere (Ian McGilchrist) 

The Failure of User Interfaces

The Abstractism Problem

Today's business intelligence interfaces exemplify what I call "abstractism"—the presentation of information in formats that do not match natural human cognitive processing patterns. The brain primarily organizes information spatially, temporally, and relationally. Traditional interfaces require translation between these innate spatial frameworks and abstract symbolic displays, creating cognitive load that reduces analytical efficiency.  

The mental effort needed to translate between spatial concepts and abstract representations can drain working memory, creating unnecessary friction and hindering strategic analysis. If you've ever wondered why people leave these sessions with headaches, now you know.