![[herding-cats-logo.png|150]]
# About the Author
**Jeep Marshall**
LTC, U.S. Army (Retired)
Airborne Infantry | Special Operations | Process Improvement
📧 [EMAIL-REDACTED]
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## Background
I served 26 years in the U.S. Army, spanning airborne infantry and special operations. Seven of those years went to training brigade-level staffs through simulation-driven exercises — where every planning framework described in this series got tested under operational pressure, repeatedly, with real consequences for failure.
I hold Lean Six Sigma Black Belt certification. I've applied DMAIC methodology to military operations, organizational systems, and — more recently — to AI agent architecture and workflow design.
Currently I'm building a comprehensive "second brain" knowledge management system using Obsidian, Claude AI, and multi-agent workflows. That system accidentally became the laboratory documented in [[Paper-3-The-PARA-Experiment|Paper 3]].
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## The Thesis
The AI industry has a discipline problem, not an intelligence problem.
I learned this in the Army. Individual brilliance doesn't survive contact with organizational complexity. A platoon of exceptional soldiers fails without doctrine. A fleet of brilliant AI agents does the same thing — just faster and at greater expense.
These papers make the case that the next generation of AI practitioners needs Black Belts and battle staff officers more than another language model.
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## How This Series Happened
I didn't plan to write seven research papers and a case study. I planned to build a better personal knowledge management system.
What happened instead: I started applying military planning frameworks to AI workflows, ran into every coordination problem the academic literature predicted, documented the failures, and kept refining the doctrine. By the time I had 1,768 git commits across 33 days of multi-agent operations, the papers were writing themselves.
Claude AI assisted throughout. The research, the analysis, the live field tests, and the cross-series synthesis all happened in real-time sessions. The ideas and the operational experience are mine. The execution partnership made them publishable.
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## Research Methodology
Each paper applies a multi-disciplinary analytical team — a methodology I borrowed from how a proper battle staff operates:
- **LSS-BB (Lean Six Sigma Black Belt):** Waste analysis, process capability assessment, DMAIC framework
- **QASA (Quality Assurance Standards Analyst):** Source verification, cross-reference validation, publication readiness
- **ASS2 (AI Systems Security Specialist):** Dependency risk, supply chain vulnerabilities, security posture
- **Creative Arts Practitioner:** Hands-on field testing, visual evidence, professional workflow assessment
- **Observer-Controller:** Scope management, quality gate enforcement, cross-series continuity
This isn't decoration. The multi-perspective lens produces findings that a single analyst misses.
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## Publications and Target Venues
The series targets both practitioner and academic audiences:
- *Small Wars Journal* (military AI doctrine, operational applications)
- *Military Review* (command and control frameworks)
- *War on the Rocks* (strategic analysis)
- *Journal of Force Structure* (organizational design)
- General practitioner audience via Obsidian Publish
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## Contact
For questions, collaboration, or speaking inquiries:
- **Email:** [EMAIL-REDACTED]
- **GitHub:** [emanblue](https://github.com/emanblue)
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*© 2026 Jeep Marshall. All rights reserved.*
*"Herding Cats in the AI Age" is an original research series by Jeep Marshall.*
## Related
- [[Index - Published]] — parent folder