AIKnowsMe – Public Documentation and Introspective Profiling Framework

AIKnowsMe™ is an experimental, research-grade GPT-powered profiling system that blends symbolic association modeling, cognitive latency analysis, and structured essay evaluation into a three-stage introspective sequence. While experimental in deployment, the system architecture and profiling logic are proprietary and not open-source. AIKnowsMe™ is built on a protected methodology that reflects original research and prompt engineering design by the author. This documentation provides a public overview of the project structure, user-facing processes, and interpretive logic of the 20-dimensional KPI evaluation model. While user experience and conceptual goals are openly described, all internal methodologies, heuristic scoring systems, and prompt engineering logic remain proprietary and protected. The profiling experience includes:- Round 1: Symbolic Reflex Mapping (Word Association)- Round 2: Scenario-Based Cognitive Testing- Round 3: Generative Essay Projection Archetypal interpretation is based on Jungian psychology and is symbolic rather than deterministic. The tool aims to help users gain deeper insight into their cognitive styles, narrative structures, and introspective tendencies. More Information - Try the tool: www.aiknowsme.io/gpt - GitHub repository: github.com/aiknowsme - LinkedIn page: linkedin.com/company/aiknowsme

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-24
DOI
https://doi.org/10.5281/zenodo.15733594
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
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article

AIKnowsMe – Public Documentation and Introspective Profiling Framework

Zenodo (CERN European Organization for Nuclear Research)
Data Visualization and Analytics
article

AIKnowsMe – Public Documentation and Introspective Profiling Framework

article en

Abstract

AIKnowsMe™ is an experimental, research-grade GPT-powered profiling system that blends symbolic association modeling, cognitive latency analysis, and structured essay evaluation into a three-stage introspective sequence. While experimental in deployment, the system architecture and profiling logic are proprietary and not open-source. AIKnowsMe™ is built on a protected methodology that reflects original research and prompt engineering design by the author. This documentation provides a public overview of the project structure, user-facing processes, and interpretive logic of the 20-dimensional KPI evaluation model. While user experience and conceptual goals are openly described, all internal methodologies, heuristic scoring systems, and prompt engineering logic remain proprietary and protected. The profiling experience includes:- Round 1: Symbolic Reflex Mapping (Word Association)- Round 2: Scenario-Based Cognitive Testing- Round 3: Generative Essay Projection Archetypal interpretation is based on Jungian psychology and is symbolic rather than deterministic. The tool aims to help users gain deeper insight into their cognitive styles, narrative structures, and introspective tendencies. More Information - Try the tool: www.aiknowsme.io/gpt - GitHub repository: github.com/aiknowsme - LinkedIn page: linkedin.com/company/aiknowsme

Zenodo (CERN European Organization for Nuclear Research)
Association for Symbolic Logic (US), Rejonowe Przedsiębiorstwo Wodociągów i Kanalizacji W Sosnowcu (Poland) (PL)
Openalex Percentile: Top 56%
Data Visualization and Analytics
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