1. Proprietary Methodology & Intellectual Property

The IfThenWhy™ Framework—including the 5-Pillar Architecture (Data, Validation, Governance, Persona, Instruction) and the 5-File structure—is a proprietary methodology protected by Copyright and Trademark law.

  • Expression: The specific arrangement, pedagogical steps, and definitions within the framework are protected works of authorship.

  • Attribution Requirement: Any utilization of this methodology must be credited with the phrase: "Utilizing the IfThenWhy™ Framework."

2. Status as Passive Information Provider

  • The IfThenWhy™ standard is a conceptual architecture. The author provides the framework; the user provides the execution. Under 2026 Florida AI Statutes, the author is not responsible for the performance or safety of systems built using this framework.

3. Allocation of Risk & Liability (The "System Operator" Clause) The User acknowledges that Artificial Intelligence and Large Language Models are inherently non-deterministic.

  • Execution vs. Framework: Failures in AI output (e.g., hallucinations or data inaccuracies) are classified as Execution Errors by the third-party AI model or the User’s implementation.

  • Indemnification: The User, as the "System Operator," assumes 100% of the risk. By using this framework, the User agrees to indemnify the Author against any claims arising from "unsupervised" algorithmic actions, data errors, or financial losses.

4. Mandatory Human-in-the-Loop (HITL)

The IfThenWhy™ methodology is designed as a decision-support tool. A core tenet of the framework is that all AI-generated outputs must be validated by a human professional. Use of the framework without human oversight is considered a deviation from the IfThenWhy™ standard.

5. Restrictions on Automated Ingestion

The use of the IfThenWhy™ Ecosystem to train, fine-tune, or provide Retrieval Augmented Generation (RAG) context for any Large Language Model (LLM) for commercial purposes is prohibited without an Institutional Grant of Recognition. This ensures the methodology is not "laundered" through an AI model to strip its attribution and standards.