From language models to computable thinking: how SymFSM changes the architecture of AI systems

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The article explains SymFSM as an alternative to standard LLM-centric AI architectures. It argues that symbolic, finite-state reasoning can improve reliability, controllability, and recursive processing in AI systems. The piece contrasts SymFSM with RAG, prompt engineering, and chain-of-thought approaches, positioning it as a way to move toward more computationally grounded AI. It also frames the approach as relevant to broader AGI-oriented system design.

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