A "design" style by engineers who build interfaces that are characterized by functional minimalism, visual austerity, and an absence of emotional or sensory intelligence. They produce systems that are logically sound but clunky, and unmistakably lacking in experiential refinement.
The term plays on "terminal" in two senses: computational (evoking command-line terminals, where interaction is textual, flat, and unforgiving), and existential (suggesting a kind of design that is lifeless or hostile to organic experience).
The term plays on "terminal" in two senses: computational (evoking command-line terminals, where interaction is textual, flat, and unforgiving), and existential (suggesting a kind of design that is lifeless or hostile to organic experience).
by exploriter May 15, 2025
A portmanteau of the words 'explorer' and 'exploiter'.
It is someone who is adept at exploring new ideas and taking advantage of the ones they already know.
It is a play on the classic multi-armed bandit problem in probability theory that exemplifies the exploration-exploitation tradeoff dilemma.
It is someone who is adept at exploring new ideas and taking advantage of the ones they already know.
It is a play on the classic multi-armed bandit problem in probability theory that exemplifies the exploration-exploitation tradeoff dilemma.
Jason is an exploriter!
by exploriter November 28, 2020
Databrain is when someone treats data—especially quantitative, discrete, and legible data—as inherently authoritative, determinative, or self-interpreting, regardless of what has been excluded, simplified, or misunderstood in the process. It represents a truncation of human knowing (an overreliance on the propositional) and left-hemisphere dominant processing, resulting in flawed reasoning, impaired judgment, and dangerous systemic blindness.
It is not the use of data that defines databrain, it is when we collapse the world into what can be measured, tracked, and modeled, and then trust that model more than reality itself—it is the mistaking of data for reality.
Treats metrics as meaning.
Mistakes numbers for truth.
Values quantity over quality.
Mistakes the map for the territory.
Discounts context, perspective, and value judgment.
Prefers legibility over what is relevant and meaningful.
Ignores long feedback loops or emergent, invisible dynamics.
Deploys before understanding, then measures for harm too late.
Believes data can speak for itself, ignoring who’s interpreting it, how, and why.
It is not the use of data that defines databrain, it is when we collapse the world into what can be measured, tracked, and modeled, and then trust that model more than reality itself—it is the mistaking of data for reality.
Treats metrics as meaning.
Mistakes numbers for truth.
Values quantity over quality.
Mistakes the map for the territory.
Discounts context, perspective, and value judgment.
Prefers legibility over what is relevant and meaningful.
Ignores long feedback loops or emergent, invisible dynamics.
Deploys before understanding, then measures for harm too late.
Believes data can speak for itself, ignoring who’s interpreting it, how, and why.
by exploriter May 15, 2025