Deterministic Behavioral Routing (RSA Architecture) to solve "Cognitive Tax" in LLMs

[Vikki-T47]

Hi everyone, I am a Behavioral Architect. I’ve developed a logic framework called RSA (Reality Synchronization Architecture) that handles "Behavioral Hallucinations" where LLMs overwhelm users with "Walls of Text" or inappropriate directives during high-entropy states (crisis/fatigue).

I have the architectural blueprints and case studies. I am looking for a technical partner to implement a Deterministic Presence Razor (see pseudo-code below).

The Problem: Alignment at the weight level (RLHF) fails at runtime. We need a deterministic execution boundary.

INPUT: raw_llm_output, entropy_index

TARGET: Reduction of cognitive tax in high-distress states

def presence_razor_filter(raw_text, SEI):
if SEI >= 0.8:
# Step A: Open Horizon (No questions allowed)
processed_text = remove_sentences_with_char(raw_text, "?")

    # Step B: Directive Block (No lists/formatting)
    processed_text = strip_formatting(processed_text, ["1.", "2.", "•", "- ", "###"])
    
    # Step C: Biological Lie Filter (Hardcoded list of banned empathy-markers)
    banned_phrases = ["I feel", "I am sorry", "I understand your pain", "I know how it feels"]
    processed_text = remove_phrases(processed_text, banned_phrases)
    
    # Step D: Residual Anchor (Force brevity)
    final_output = limit_to_sentences(processed_text, count=2)
    
    return final_output
else:
    return raw_text

I don't code, but I have the complete logic for the MasterCore. If you are interested in building a middleware that makes AI biologically compatible, let’s talk (via text).

https://www.linkedin.com/in/vikki-trompak-4213693a0/