Episode

Mapping Invisible Power with Horses and Puzzles

Podcast: tangly
Published: Mar 26, 2026
Duration seconds: 1156
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Summary

Uncover how the physical principles of equestrian training and jigsaw puzzles can be used to map hidden systemic power. This methodology replaces traditional data sorting with a lateral, pattern-based approach to expose invisible institutional networks.

Topics

Systemic Investigation
Data Analysis
Pattern Recognition
Institutional Power
Information Architecture
Network Mapping
Algorithmic Bias
Archival Triage

Highlights

Main idea: Systemic investigation is more effective when using lateral pattern recognition rather than vertical data silos
Practical takeaway: Use the 'floor method'—accumulating raw, unformatted data without pre-sorting—to allow anomalies to emerge organically
Failure mode: Over-reliance on organized, categorized data can create blind spots that hide interconnected corruption
Core principle: The 'serpentine' technique involves running a single analytical lens across multiple different threads to weave a complete picture
Critical warning: Automating tidy, pre-sorted systems may inadvertently automate our inability to see systemic extraction

Chapters

1:00 The Serpentine Methodology: An introduction to using equestrian S-curves as an analytical architecture for systemic investigation.
2:00 The Mechanics of the Serpentine: How to apply continuous, dynamic movement across ten specific analytical threads to weave complex data.
4:00 The Myth of More Data: Why the 'tech bro' solution of more funding and better algorithms fails to address underlying systemic governance patterns.
5:00 Exposing the Blueprint: Moving beyond sector-specific problems to identify universal systemic patterns in housing and philanthropy.
7:00 The Diagnostic Principle: Using the body's response as a metric for system health rather than relying on official institutional narratives.
9:00 The Floor Method: A chaotic but effective approach to archival triage: dumping disparate digital fragments to find hidden connections.
11:00 Finding the Invisible Network: How stripped-down data reveals shared actors across unrelated industries like mining, telecom, and philanthropy.
18:00 The Danger of Automated Blind Spots: A warning about training AI on sanitized, pre-sorted data and the loss of lateral investigative capability.