Notes and research

Guides

• AI agents and workflows: tasks, tool access, and human review.
• AI governance: responsibilities, limits, and operating requirements.
• AI agent security: credential handling, permissions, and data exposure.
• AI data governance: sources, access rules, and retention.
• AI audit trails: records for reviewing actions and outcomes.
• Logging for AI-assisted development: records to plan while building a prototype.
• AI risk management: risks, controls, and review responsibilities.
• AI privacy review records: purpose, data flow, and safeguards.

Workshop working paper

Enhancing Organizational Technology Adoption Through AI-Driven Scenario-Based Learning

This working paper describes the scenario-based approach used in our workshops and discusses research on organizational learning and technology adoption.

Request the working paper, or read about the workshop approach.

TN-Proto

TN-Proto provides message-level primitives for encryption, verification, use contracts, and source references. Read the overview or the protocol documentation.