"This article is not about AI. It's about why memory, not models, is the difference between compounding value and constant reset. It is about what happens when systems that sound intelligent cannot sustain continuity, and why that failure quietly breaks the economic logic of advertising. When continuity disappears, compounding stops. When meaning stops compounding, efficiency collapses. Spending rises, trust erodes, and the system looks like it is working right up until the moment it becomes unaffordable."
"Predictive systems worked because they did not need to explain themselves. They identified patterns, produced scores, and left interpretation to humans. The machine predicted. The human narrated. Strategy lived in the space between signal and story. It was imperfect, but it was stable. Generative AI collapsed that separation. The moment systems were asked to explain themselves conversationally, they stopped behaving like analytical tools and started behaving like narrators."
Memory, not model capability, determines whether meaning compounds across interactions and creates lasting economic value. Advertising systems optimized for prediction produced scores that humans interpreted, enabling imperfect but stable continuity. Generative AI transformed predictive tools into narrators that explain and assert, collapsing the separation between signal and story and shifting authority to machines. When continuity breaks, compounding halts: efficiency collapses, spending rises, trust erodes, and outcomes become unaffordable. The next phase of AI adoption risks large-scale waste unless memory and continuity are preserved, and unless memory ownership resides with people rather than platforms.
Read at Forbes
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