AI work leaves plenty of trace. The problem is that those traces are scattered across platforms, organized around conversation flow, and not structured around the questions an audit actually asks. CARCS closes that gap with a ten-section governed record built from a three-part prompt suite. It works on any AI platform. Named human sign-off is required before finalization. This working paper releases the protocol for feedback and collaboration from governance practitioners, compliance officers, and researchers.
HAIA
AI Governance Beyond the Warning: From Tristan Harris’s Diagnosis to the Infrastructure It Requires
A Governance Practitioner’s Response to the Diary of a CEO Interview (PDF Here) Executive Summary Tristan Harris’s November 2025 conversation on The Diary of a CEO reached millions of viewers with a structural diagnosis of the AI race: the same incentive architecture that produced social media’s damage to democracy and mental health is now operating […]
Empire of Evidence: Testing Karen Hao’s Claims Against the Governance Infrastructure They Require
A Governance Practitioner’s Examination of the Diary of a CEO Interview and Empire of AI A journalist with engineering training spent eight years investigating the AI industry and concluded that the major companies operate as empires. A governance practitioner who builds open-source infrastructure for the same industry watched the two-hour interview where she made that […]
HAIA: Human Artificial Intelligence Assistant
The Name Given to the Ecosystem for Human-AI Collaboration (PDF) What It Is, Why It Exists, Where It Comes From Executive Summary HAIA stands for Human Artificial Intelligence Assistant. It is the ecosystem that structures a human’s interaction with AI, specifically with large language models, across every stage of collaboration: how the AI is instructed, […]
Checkpoint-Based Governance (CBG): A Constitutional Framework for Human-AI Collaboration
The Four Constitutional Properties Property 1Primary Purpose CBG is AI Governance. It provides human oversight and accountability for AI-assisted work. CBG’s primary purpose is to supply the governance layer that sits on top of single-platform AI output and that makes RECCLIN dispatch and CAIPR parallel review into governed learning systems rather than AI frameworks alone. […]
The Human Enhancement Quotient (HEQ): Measuring Cognitive Amplification Through AI Collaboration (draft)
The HAIA-RECCLIN Model and my work on Human-AI Collaborative Intelligence are intentionally shared as open drafts. These are not static papers but living frameworks meant to spark dialogue, critique, and co-creation. The goal is to build practical systems for orchestrating multi-AI collaboration with human oversight, and to measure intelligence development over time. I welcome feedback, […]