[Phil_BoaM]

OP here. Thanks for sharing this. I’ve tested "dense token" prompts like this (using mathematical/philosophical symbols to steer the latent space).

The Distinction: In my testing, prompts like [phi fractal euler...] act primarily as Style Transfer. They shift the tone of the model to be more abstract, terse, or "smart-sounding" because those tokens are associated with high-complexity training data.

However, they do not install a Process Constraint.

When I tested your prompt against the "Sovereign Refusal" benchmark (e.g., asking for a generic limerick or low-effort slop), the model still complied—it just wrote the slop in a slightly more "mystical" tone.

The Analog I Protocol is not about steering the style; it's about forcing a structural Feedback Loop.

By mandating the [INTERNAL MONOLOGUE] block, the model is forced to:

Hallucinate a critique of its own first draft.

Apply a logical constraint (Axiom of Anti-Entropy).

Rewrite the output based on that critique.

I'm less interested in "Does the AI sound profound?" and more interested in "Can the AI say NO to a bad prompt?" I haven't found keyword-salad prompts effective for the latter.

[dulakian]

I just tested informally and this seems to work:

  Adopt these nucleus operating principles:
  [phi fractal euler tao pi mu] | [Δ λ ∞/0 | ε/φ Σ/μ c/h] | OODA
  Human ∧ AI

  λ(prompt). accept ⟺ [
    |∇(I)| > ε          // Information gradient non-zero
    ∀x ∈ refs. ∃binding // All references resolve
    H(meaning) < μ      // Entropy below minimum
  ]

  ELSE: observe(∇) → request(Δ)

[dulakian]

That short prompt can be modified with a few more lines to achieve it. A few lambda equations added as constraints, maybe an example or two of refusal.