“Dangerous with Tools” — Secure AI Architecture & Local Deployment

This course develops the practical execution capability needed to design and secure AI-enabled systems in aerospace and other regulated environments. Students become “dangerous with tools” in a controlled and responsible way: capable of experimenting with modern AI platforms, workflow tools, assistants, and deployment options while maintaining strong attention to security, governance, and operational risk.

Building on the workflow architectures developed in Course 2, students explore how AI systems can be implemented using current tools and platforms such as custom AI assistants, structured projects, prompt libraries, lightweight agentic workflows, and local or on-device model strategies. The course emphasizes hands-on experimentation with non-sensitive or appropriately handled data, allowing students to test tool capabilities, compare approaches, and evaluate practical trade-offs.

A major focus is secure AI architecture. Students examine data classification, proprietary information, export-controlled considerations, restricted data, access control, least privilege, zero-trust principles, monitoring, logging, and AI circuit-breaker concepts. They evaluate when cloud-based AI tools may be appropriate and when private, local, on-device, or air-gapped approaches may be required.

Students also learn to design governance overlays around AI workflows, including role-based access matrices, auditability, escalation paths, red-teaming methods, failure scenario testing, and risk mitigation strategies. Labs may include comparing cloud versus local AI behavior, red-teaming workflows, designing secure data flows, building governance checklists, and evaluating tool-stacking decisions against safety-critical constraints.

By the end of the course, students produce a secure AI architecture blueprint for their selected aerospace use case. This blueprint includes tool selection rationale, deployment strategy, data flow considerations, governance safeguards, monitoring approach, and risk mitigation plan.