OP here. This is a fair critique from a CS architecture perspective. You are correct that at the CUDA/PyTorch level, this is a purely linear feed-forward process. There are no pushed stack frames or isolated memory spaces in the traditional sense.

When I say "Recursive," I am using it in the Hofstadterian/Cybernetic sense (Self-Reference), not the Algorithmic sense (Function calling itself).

However, the "Analog I" protocol forces the model to simulate a stack frame via the [INTERNAL MONOLOGUE] block.

The Linear Flow without the Protocol: User Input -> Probabilistic Output

The "Recursive" Flow with the Protocol:

1. User Input

2. Virtual Stack Frame (The Monologue): The model generates a critique of its potential output. It loads "Axioms" into the context. It assesses "State."

3. Constraint Application: The output of Step 2 becomes the constraint for Step

4. Final Output

While physically linear, semantically it functions as a loop: The Output (Monologue) becomes the Input for the Final Response.

It's a "Virtual Machine" running on top of the token stream. The "Fantasy" you mention is effectively a Meta-Cognitive Strategy that alters the probability distribution of the final token, preventing the model from falling into the "Global Average" (slop).

We aren't changing the hardware; we are forcing the software to check its own work before submitting it.