LLMs differ from social media in psychological influence: social media is broadcast and performative, amplifying feelings about others, while LLMs are private 1:1 interactions that amplify feelings about ourselves and represent a new class of relationship and layer of cognition.

Testing Miller's number for LLMs by progressively adding rules to prompts reveals that around 15-16 interconnected instructions in a single cause cognitive overload for larger models.

A carefully crafted prompt asking LLMs to explain Heidegger's 'readiness-to-hand' while annotating their own cognitive processes yields surprising responses about the suppressed implications of the concept for both human existence and AI architecture.

The Yerkes-Dodson law reveals a pattern in how performance relates to pressure. Performance increases to a point, then drops with further arousal. The pattern holds a key detail — this decline appears only for difficult tasks.

AI assistance shifts work from deep work (focused production) to deep orchestration (supervisory judgment and integration). This new mode increases decision volume, control overhead, and cognitive load, while potentially making us more suggestible when executive control is depleted.

Many power users developed their own informal taxonomies for differences in LLMs behavior. One model is the poet-philosopher, another the pragmatic engineer, a third the cynical analyst. These mental shortcuts help to choose which model to use for which task, how to phrase prompts, what to expect in return. But metaphors and intuition only take us so far, especially when we're building production systems that need consistency and predictability.

Some people are satisfied with art's craft and surface. A striking image, a perfectly balanced object, a song that's tight and in tune. With generative AI, this kind of art is now abundant and nearly frictionless to produce and consume. Beauty isn't obsolete - but it's a weak differentiator. But others are seeking something else entirely. To experience. To feel part of a moment. Even to co-create, however briefly, with the artist and with each other.

Tech systems, just like states, look for things that they can measure - and ignore what they can't. First, they learn which kinds of work are "legible" enough to matter - the "quantifiable" tasks, the "scalable" skills, the "data-driven" professions. Then, having made those jobs visible, they proceed to automate them.

Simulating human behavior is an universal LLM steering strategy.

Creativity emerges from the interplay between Kahneman's cognitive systems and Csikszentmihalyi's cultural selection.