Description not evaluation - The Cynefin Co

The Shape of Knowing - The Cynefin Co

We evolved to make sense of a world that does not come with explanations attached. This is the third in a series on the trialectics. For an introduction

Managing for emergence through abduction - The Cynefin Co

Several interactions over social media have left me somewhat frustrated by the inability of several people who could know better (I exclude the odd

Descriptions Aren’t Prescriptions

When we look at a representation of reality, we can choose to either see it as descriptive, meaning it tells us what the world is currently like, or as prescriptive, meaning it tells us how the world should be. Descriptions teach us, but they also give us room to innovate. Prescriptions can get us stuck. One place this tension shows up is in language.

Category: The Essence of Composition

I was overwhelmed by the positive response to my previous post, the Preface to Category Theory for Programmers. At the same time, it scared the heck out of me because I realized what high expectati…

Cyclomatic complexity

Cyclomatic complexity is a software metric used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code. It was developed by Thomas J. McCabe, Sr. in 1976.

Pluralistic: Model collapse (12 Aug 2026) – Pluralistic: Daily links from Cory Doctorow

One of my favorite rhetorical and analytical moves is joining things together (showing that two different, seemingly unrelated ideas are aspects of the same phenomenon) and taking them apart (resolving a paradox by demonstrating that what appears to be one, contradictory thing is actually two different things that have been lumped together).

What Makes a Concept Good? A Criterial Framework for Understanding Concept Formation in the Social Sciences

Nowhere in the broad and heterogeneous work on concept formation has the question of conceptual utility been satisfactorily addressed. Goodness in concept formation, I argue, cannot be reduced to 'clarity,' to empirical or theoretical relevance, to a set of rules, or to the methodology particular to a given study. Rather, I argue that conceptual adequacy should be perceived as an attempt to respond to a standard set of criteria, whose demands are felt in the formation and use of all social science concepts: (1) familiarity, (2) resonance, (3) parsimony, (4) coherence, (5) differentiation, (6) depth, (7) theoretical utility, and (8) field utility. The significance of this study is to be found not simply in answering this important question, but also in providing a complete and reasonably concise framework for explaining the process of concept formation within the social sciences. Rather than conceiving of concept formation as a method (with a fixed set of rules and a definite outcome), I view it as a highly variable process involving trade-offs among these eight demands.

ATProto explained for a slightly "technical" audience - Foxes

ATProto explained for a slightly "technical" audience - Foxes

Henrik Karlsson on Twitter / X

When I read lively prose, one thing I notice is that it packs a lot of information per sentence—but not, usually, by being compact. Instead, how to explain it?Take this phrase “an interesting and exciting new finding”—that’s pretty dead. And one of several reasons is that the…— Henrik Karlsson (@phokarlsson) February 24, 2026

A Philosopher’s One-Word Theory to Explain Why the World Feels So Weird

Once you learn what the "uni-context" is, you won't stop seeing it everywhere

Addressing the Precision-Breadth-Simplicity Impossible Trinity in Psychological Research: A Comprehensive Exploration Approach

Psychological research faces a fundamental challenge—the Precision-Breadth-Simplicity (PBS) impossible trinity. While experimental findings are often precise and simple, they tend to be narrow in scope. Conversely, broad-and-simple concepts frequently lack precision. Developing theories that are both precise and broad is scientifically valuable but inevitably introduces complexity, which conflicts with humans’ cognitive limitations in processing complexity. To address this impossible trinity, I propose a comprehensive exploration (CE) approach—a data-guided theory-building framework that involves: (1) designing experimental conditions in a stimulus-driven way, with minimal upfront theoretical specification; (2) conducting experiments with tens of millions of observations (e.g., 40 million responses in Huang, 2025a); (3) modeling the results through iterative improvements; and (4) producing the outcome: a moderately complex quantitative information-processing model to integrate diverse empirical findings. Inspired by similar strategies that drove breakthroughs in artificial intelligence (e.g., ImageNet’s role in advancing object recognition), the CE approach offers a promising path toward more integrative psychological theories. Initial implementations in visual working memory research demonstrate both its practicality and potential to transform how we study mental processes.