CEM Research Project

The CEM Research Project publishes open research on the Compounding Execution Method (CEM) — a framework for turning AI-enabled work into compounding output.
The project produces methodology papers, datasets, and measurement architecture from a single operator (Operator 1) running multiple operational systems with continuous execution data from July 2025 to present.
All findings are published openly for evaluation, citation, and operator onboarding. Research content is licensed CC BY-NC-SA 4.0. The dataset is n=1 until additional operators onboard — disclosed in every publication.

Research stack: open methodology, DOI-anchored publications via Zenodo, ORCID-verified authorship.
Measurement stack: continuous data collection from git history, AI session logs, financial records, and biometric data. Cross-referenced, multi-stream evidence.
Publication stack: Zenodo (DOI papers and datasets), dev.to (technical writing), Substack (research notes), ORCID (researcher identity). All linked under the CEM Research Project entity.
Framework content: 22 concepts, 9 execution tools, 3 guardrails. Measurement layer: 14 signals, 5 dimensions, 4 pillars.