Standard Large Language Models (LLMs) are engineered for workplace efficiency—to give the fastest, most direct answer possible. For children, efficiency is the enemy of learning.
Solves the problem instantly, bypassing the productive struggle required for a child's neural growth.
Designed to keep users chatting for hours, creating deep dopamine dependencies.
Trains proprietary models on your child's conversational data and personal queries.
Strictly barred from giving direct answers. Guides children using hints, analogies, and questions.
Mathematically enforced time limits to eliminate screen addiction and promote digital autonomy.
Evaluates Logic Synthesis and Problem Formulation, providing transparent cognitive scorecards to parents.
We believe the rules governing how AI interacts with children should be public, auditable, and transparent. The Artificial Intention™ Framework is open-sourced under the MIT License for developers, educators, and parents.
View Framework on GitHubIncludes full documentation, system prompts, and the 5-Axis Logic evaluation code.