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Every paper in this series applies a multi-disciplinary analytical team modeled on a military battle staff. Each perspective generates findings the others miss.

RoleFunctionFramework
LSS-BBLean Six Sigma Black BeltDMAIC, DOWNTIME waste taxonomy, process capability assessment, statistical analysis
QASAQuality Assurance Standards AnalystSource verification, citation integrity, cross-reference validation, publication readiness
ASS2Automation, Structure & Scalability, Safety & SecurityThree-domain review applied together: automation potential, structural scalability, and safety/security posture. Flat, equal-weight framework — not a single-lens analysis.
Creative ArtsField Test PractitionerHands-on product testing, visual evidence capture, professional workflow simulation
Observer-ControllerScope and Quality ManagerPhase gate enforcement, cross-series continuity, scope creep prevention

PaperTitleCore QuestionKey Evidence
1The Super Intelligent Five-Year-OldWhy does AI need doctrine?Google/MIT 39-70% degradation; UC Berkeley 14 failure modes; Gartner 40% cancellation prediction
2The Digital Battle StaffDid the military already solve this?230 years of C2 doctrine; Pentagon AI Acceleration Strategy; Army MOS 49B; SOCOM agentic AI
3The PARA ExperimentWhat happens in a live multi-agent lab?1,768 commits; 33 days; 12 of 14 MAST failure modes observed; 3.83x velocity increase
4The Creative MiddlemanWhat does the middleman trap look like?Adobe Firefly field test; “BEARETIXSLUGE” vs readable text; 43% stock decline; DOWNTIME waste
5When the Cats Talk to Each OtherWhat happens when AI models talk?Claude-Grok live exchange; CMDP 8-component framework; 15-20% fidelity improvement; physics pilot
6When the Cats Form a TeamWhat happens when four AI models staff a decision?4-model MDMP ensemble; 6 strategic insights solo missed; structured dissent catches blind spots
6bWhen the Cats Take the Same TestWhat happens with identical instructions?51% quality variance (n=6); bimodal distribution; provenance crisis; composite protocol ready
7MDMP Platform BlueprintCan doctrine-structured decision-making be productized?Conversational MDMP platform spec; ROTC-to-enterprise scale; distributed authority model; human-in-the-loop architecture
8The Toboggan DoctrineWhy channels, not walls, for AI governance?Gravity-fed pipeline doctrine; template-driven governance; OODA + DMAIC integration; structural enforcement over behavioral instruction

#TitleCore QuestionKey Evidence
1When the AI Stopped Moving Its Own FilesCan Lean Six Sigma replace a 477-line AI agent?1,160-line shell script replaces agent; 87% tool call reduction; 83% time reduction; process sigma 3.2 → 4.6