Beyond Generative and Agentic AI -- The Unifying Theme

Beyond Generative and Agentic AI_ENG_FR.pdf

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The Unifying Theme_ENG_FR.pdf

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From Performance to Legitimacy.pdf

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The document critiques the evaluation of systems (AI, economics, cognition) based on visible performance, showing that functional appearance is often mistaken for actual intelligence, value, or stability.

It argues that internal structure—constraints, regulation, and dynamics—precedes function, and that surface metrics lead to fragile overestimations.

The CBD (Constraints-Equilibrium-Dynamics) framework is proposed as a unifying principle for judging the consistency, robustness, and legitimacy of complex systems.

The following document argues that the distinction between generative and agentic AI is superficial, as these systems share the same structural limitations despite different behaviors.

The real problem is the lack of cumulative internal dynamics: without irreversible memory, internal thresholds, and endogenous feedback, AI remains unstable and superficial.

The CBD framework proposes an architecture based on persistent internal constraints, a necessary condition for reliable, manageable, and sustainable AI.