Thinking in Fragments: A Human–Machine Model of Intelligence

Most discussions about intelligence assume something that isn’t true: that thinking begins with complete thoughts, clear goals, and well-formed instructions. But real human cognition doesn’t work that way. Real thinking begins long before language, before decisions, before plans. It begins in the messy pre-layer of the mind—half-formed ideas, vague sensations, flashes of intuition, and emotional signals that don’t yet have words. These fragments are the true building blocks of thought, and if AI is going to collaborate with humans meaningfully, it has to meet us in that fragment space, not just in polished sentences.

Look at people closely and you’ll see two broad modes of cognition. Some humans operate mostly in simple loops: immediate needs, familiar routines, predictable desires, shallow processing. They’re not trying to redesign the world; they’re trying to function inside it. Most consumer technology is built for this group because it’s easy to model, profitable, and predictable.

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