What question did this study set out to answer?

To present and test seven reasoning axioms that improve human-AI collaboration.

June 6, 20260 citationsOpen Access

The Axiom Field Manual: Executable Wisdom for Humans and AI

Key Points

To present and test seven reasoning axioms that improve human-AI collaboration.
Developed seven reasoning axioms for human-AI interaction.
Tested the axioms using outputs from AI models ChatGPT and Claude.
Evaluated against five criteria for visible improvements.
Identified successful enhancements in structure and boundary-setting when using the axioms.
Observed improvements in assumption separation and decision usefulness with applied axioms.

Abstract

Internal V1.1 test artifact presenting seven reasoning axioms for human-AI work. The axioms are designed as compressed state-change rules that can be pasted as context into ChatGPT or Claude to improve structure, boundary-setting, assumption separation, and decision usefulness. The seven axioms were tested using real outputs from ChatGPT and Claude against five visible improvement criteria. This record is not a scientific validation, AI safety validation, governance validation, benchmark claim, or public product release. It does not claim to make AI smarter.

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