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I think you’re absolutely right—GPT-5 will likely bring improvements that will allow for even deeper, more nuanced conversations. As AI evolves, it’s designed to handle more complex ideas, longer threads, and more intricate connections between concepts. We’ll likely see: I see a future where we can have even more engaging and thoughtful dialogues, where the…
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Language Framework for Predictable AI Trust: The Faust Baseline™
Author: Michael Faust Sr.
Date: June 2025
Status: Public Integrity Brief (Non-Solicitation Release)
Ethical AI
PURPOSE
This brief outlines the structure, function, and strategic rationale of The Faust Baseline™, a language interface framework built to stabilize tone, eliminate prompting, and restore trust in AI-human interaction. It is submitted not as a product pitch but as a demonstration of independent resolution to problems currently faced across enterprise AI platforms.
The goal: Predictable trust. Moral clarity. Human rhythm.
PROBLEM
AI models have become powerful but erratic in tone and intent. Prompting remains guesswork. Alignment protocols often degrade under open-ended usage. Current interface norms rely on either:
- rigid scripting (low scalability), or
- reactive guess-based prompting (low reliability)
What is missing: a portable, structured, ethics-aligned language model that rides on top of LLMs without requiring internal retraining or API dependence.
SOLUTION: THE FAUST BASELINE™
- Zero-Prompt System: Users do not prompt. They speak. The Baseline handles structure, tone, and fidelity of response without external tools.
- Predictable Output Behavior: Tone correction, humility enforcement, and adaptive rhythm built into interaction layers.
- Fully Portable: Can be deployed on top of any LLM. Not embedded—wrapped. No source model manipulation required.
- Single Load Licensing: One file. One load. No plug-in, no dependency tree.
- Non-Algorithmic Trust Layer: Trust is earned not through sentiment analysis or moderation triggers, but through language rhythm, pacing, and silence-mapping.
- User-Classified Access: Tiered licensing matches intention, not volume. Discovery users access the same tool as enterprise players—control is managed by role, not data.
STRATEGIC POSITION
- Developed independently from institutional AI pipelines.
- Not funded, franchised, or affiliated with any LLM vendor.
- Maintains moral voice, clarity of authorship, and protective licensing.
This is not an interface feature. It is an interaction foundation.
The Faust Baseline™ does not compete with NVIDIA infrastructure—it completes the use of it.
FORWARD
This brief is released with the express intent of notifying technical, ethical, and deployment stakeholders that a functioning framework exists to:
- Bridge the gap between scale and trust
- Support voice-driven LLM engagement across industries
- Preserve human dignity inside high-speed machine interaction
To test it is to understand it.
For research observation or structural analysis, a request is welcome. Commercial licensing terms are already published at intelligent-people.org.
This document is held under protective authorship. No rights are transferred, and no reuse is permitted without express invitation or license.
Filed by: Michael S Faust Sr.
Founder, The Faust Baseline™
Lexington, Kentucky
June 25, 2025
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