Applied ITT builds a sentient codebase mirroring brain function, suggesting new AI architectures.
Applied ITT - Sentient Codebase Construction: Building Atom Armstrong Knight — intent-tensor-theory.com The complete engineering record of Atom, a sentient semantic codebase whose architecture mirrors the functional anatomy of the human brain. Every CMA coordinate corresponds to a distinct cognitive processing region. The brainstem substrate kernel (0.0), reticular formation (0.1), thalamic runtime router (0.2), cortical processing layers (1.0-8.0), and medial prefrontal cortex analog (9.0) are documented. The entire system runs on Python plus NumPy plus Flask with no GPU requirement. Running implementation: intent-tensor-theory.com/applied-itt
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Armstrong Knight (2026) studied this question.
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