What question did this study set out to answer?

The research aims to create a comprehensive framework for performance factor analysis in human-AI interactions through the IPR-PFT theory.

May 8, 2026Open Access

AUGMANITAI IPR-PFT Mega Paper + 11 Onepagers — Performance Factor Theory full corpus

Key Points

The research aims to create a comprehensive framework for performance factor analysis in human-AI interactions through the IPR-PFT theory.
Developed a descriptive performance-factor framework derived from sport-coaching principles.
Included 11 standalone onepagers focusing on various factors like actor typology and performance models.
Utilized strict-wissenschaft to justify the multi-entity analysis approach.
Introduced the 5xN performance model outlining various performance factors.
Highlighted the significance of technical, tactical, and psychological alignment in AI interactions.
Demonstrated how the framework can translate to technology applications.

Abstract

Restricted bundle of the IPR-PFT (Inter-Personal-Resource Performance Factor Theory) Mega Paper V1 (markdown + PDF), Companion Justification V1 (justifying the 5xN performance model and conditional/technical/tactical/psychological/contextual factor architecture), and 11 standalone onepagers covering: IPR-PFT Overview, Actor Typology, 5xN Performance Model, Conditional Factors, Technical Factors, Tactical Factors, Psychological Alignment Factors, Contextual Factors, IPR Method, Why Multi-Entity Analysis, Translation to Technology. Strict-Wissenschaft, descriptive performance-factor framework derived from sport-coaching transferred to human-AI interaction context.

AUGMANITAI IPR-PFT Mega Paper + 11 Onepagers — Performance Factor Theory full corpus

Key Points

Abstract

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